Journal of Intelligent & Fuzzy Systems - Volume Pre-press, issue Pre-press

Authors: Liu, Lin

Article Type: Research Article

Abstract: There is a certain subjectivity in the teaching evaluation process, which leads to a low accuracy of the intelligent scoring system. In order to promote the intelligent development of teaching evaluation, based on machine learning, this study briefly introduces the background and current status of teaching evaluation, and describes in detail the relevant algorithm principles of data analysis and modeling using data mining technology and machine learning methods. Moreover, this study describes the establishment process of the traditional classroom teaching evaluation system and uses the classification algorithm in machine learning in the construction of evaluation models to further improve the …scientificity and feasibility of teaching evaluation. In addition, in this study, empirical algorithm is used as the basic algorithm to evaluate teaching quality, and the topic word distribution obtained by joint model training is used as the original knowledge. Finally, this research analyzes the performance of this research system through a control experiment. The research results show that the scores of the research model are close to the standard manual scores and can provide a theoretical reference for subsequent related research. Show more

Keywords: Bayesian algorithm, improved algorithm, teaching evaluation, text features

DOI: 10.3233/JIFS-189320

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Zhang, Zhijun | Ren, Xiaojun

Article Type: Research Article

Abstract: Although the data trading platform has accelerated the flow of data, the current data trading platform still has many problems. According to the characteristics of the blockchain technology, from the aspects of the attack behavior in the blockchain and the security application of the blockchain technology in power transactions, this paper studies the security of the blockchain. Moreover, this article focuses on the privacy protection of the ciphertext strategy in the CP-ABE scheme, and protects the privacy information of the access strategy by designing appropriate ciphertext and key structures and access structure forms. In addition, the system efficiency is improved …by computing outsourcing, and solutions to problems in outsourcing computing are proposed. Meanwhile, two efficient and flexible support policy hidden multi-authorization center access control schemes are constructed. Finally, this study analyzes the performance of the model through controlled experiments. The research results show that this scheme has excellent performance. Show more

Keywords: CP-ABE, blockchain, data security, data sharing

DOI: 10.3233/JIFS-189318

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Fang, Chuanxin

Article Type: Research Article

Abstract: English Online teaching quality evaluation refers to the process of using effective technical means to comprehensively collect, sort and analyze the teaching status and make value judgments to improve teaching activities and improve teaching quality. The research work of this paper is mainly around the design of teaching quality evaluation model based on machine learning theory and has done in-depth research on the preprocessing of evaluation indicators and the construction of support vector machine teaching quality evaluation model. Moreover, this study uses improved principal component analysis to reduce the dimensionality of the evaluation index, thus avoiding the impact of the …overly complicated network model on the prediction effect. In addition, in order to verify that the model proposed in this study has more advantages in evaluating teaching quality than other shallow models, the parameters of the model are tuned, and a control experiment is designed to verify the performance of the model. The research results show that this research model has a certain effect on the evaluation of school teaching quality, and it can be applied to practice. Show more

Keywords: Support vector machine, decision tree, online teaching, teaching quality, feature recognition

DOI: 10.3233/JIFS-189313

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Zhang, Gaiqin

Article Type: Research Article

Abstract: At present, experts and scholars have conducted more research on the ability of colleges and universities to transform scientific and technological achievements. However, they pay more attention to the holistic research on the transformation of scientific and technological achievements in colleges and universities across the country, while rarely divide the research objects in detail. In order to improve the evaluation effect of scientific and technological achievements in colleges and universities, this paper builds a university science and technology achievement evaluation system based on machine learning and image feature retrieval on the basis of analyzing the needs of high-tech achievement evaluation. …The system has certain flexibility. Moreover, this study selects the appropriate network architecture based on the actual data and mission objectives of the high-tech achievement evaluation. In addition, this paper proposes a FT-GRU model of a gated recurrent unit network incorporating N nearest neighbor text, and a more stable model structure is obtained through system optimization. Finally, this study designs experiments to verify the performance of the model. The research results show that the university science and technology achievement evaluation system based on machine learning and image feature retrieval constructed in this study meets the expected goals and has certain practical significance. Show more

Keywords: Machine learning, image features, feature retrieval, scientific and technological achievements in colleges and universities

DOI: 10.3233/JIFS-189319

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Li, Na

Article Type: Research Article

Abstract: Text-to-voice conversion is the core technology of intelligent translation system and intelligent teaching system, which is of great significance to English teaching and expansion. However, there are certain problems with the characteristics of factors in the current text-to- voice conversion. In order to improve the efficiency of text-to- voice conversion, this study improves the traditional machine learning algorithm and proposes an improved model that combines statistical language, factor analysis, and support vector machines. Moreover, the model is constructed as a training module and a testing module. The model combines statistical methods and rule methods in a unified framework to make …full use of English language features to achieve automatic conversion of letter strings and phonetic features. In addition, in order to meet the needs of English text-to- voice conversion, this study builds a framework model, this study analyzes the performance of the model, and designs a control experiment to compare the performance of the model. The research results show that the method proposed in this paper has a certain effect. Show more

Keywords: Machine learning, improved algorithm, phonetic conversion, English, text-to-voice conversion

DOI: 10.3233/JIFS-189316

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Li, Linghan | Feng, Yan | Li, Lei

Article Type: Research Article

Abstract: As the COVID-19 epidemic continues to spread, the government has managed to prevent people from gathering. The audit work can only be carried out through the network, which puts forward higher requirements for the accuracy and effectiveness of the audit work. Under the background of the continuous development of big data and other information technologies, big data audit has gained important technical support and played an increasingly important role. Units at all levels gradually attach importance to the enterprise management mode based on the financial sharing service mode. This paper analyzes the related problems of big data audit under the …financial sharing service mode, involving big data flow, big data preprocessing, big data audit process and other issues, in order to provide useful reference for the implementation of big data audit by using the financial sharing service mode under the influence of COVID-19. Show more

Keywords: Big data, COVID-19, audit, financial sharing service model

DOI: 10.3233/JIFS-189298

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Yan, Hongru | Chai, Huaqi | Dai, Yang

Article Type: Research Article

Abstract: According to the previous management of early warning and risk control methods, the efficiency of management prediction is low, the effect is not good, and the disadvantages are very obvious. This paper mainly studies the C4.5 algorithm, Apriori algorithm and K-means algorithm. On the basis of association rules, the data from the above three algorithms are fused. On the fusion results of the processed data, it builds and optimizes the early warning model. The fusion data used in this model can be regarded as the basic data and the association rules are used for data mining. The experimental results show …that data fusion can solve the problems of management early warning and risk control. This method is applied to enterprises Management has reference value. Show more

Keywords: C4.5 algorithm, association rules, early warning model, association analysis, K-means algorithm

DOI: 10.3233/JIFS-189297

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Zhao, Shujuan | Luo, Junqian | Wei, Shiqing

Article Type: Research Article

Abstract: Online classroom teaching is difficult to identify students’ learning status in real time. Therefore, we need to combine intelligent image recognition technology to analyze student status through eye movement features. This study solves the problem of inaccurate positioning of the initial position of the shape model in the process of eyelid matching through machine learning. Moreover, this study improves the algorithm and uses the AK-EYE model based on the combination of ASM algorithm and Kalman filtering to establish a local feature model for each feature point. According to the gray information in the normal direction of the feature point, the …local gray information is modeled. After training through the sample set to obtain the state model, the target eye can be searched, and the pose parameters can be determined. Finally, this study designs a control experiment to analyze the performance of the model proposed in this study. The research shows that the algorithm proposed in this paper has a high recognition accuracy and has a practical basis, which can be used as one of the subsequent classroom teaching system algorithms. Show more

Keywords: Machine learning, classroom recognition, student characteristics, eyeball characteristics

DOI: 10.3233/JIFS-189321

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Shijie, Ding, | Zhiwei, Zhang, | Jun, Xie,

Article Type: Research Article

Abstract: With the spread of the COVID-19 epidemic, the government has put forward higher requirements for network security and reliability through the flow of network managers and the release of information. Traditional intrusion detection technology and firewall technology cannot effectively defend against DDoS attacks. This paper analyzes the principles and defects of intrusion detection system and firewall. In this paper, the architecture design of intrusion prevention system which integrates audit and network defense functions is proposed. The system optimizes the detection and analysis component of detecting attack behavior according to the special requirements of attack defense task, and adds the module …of attack behavior characteristic analysis and defense strategy generation. The policy execution component uses a special defense engine to execute defense policies, providing the system with deep defense capabilities. Experiments show that the validity and reliability of the key modules in the proposed defense model meet the technical requirements. It has a certain reference value to improve the reliability of network management system under the influence of COVID-19 epidemic situation. Show more

Keywords: Intrusion detection, firewall, COVID-19, DDoS attack, defense strategy generation

DOI: 10.3233/JIFS-189294

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Wan, Xiaoming

Article Type: Research Article

Abstract: Because of the global spread of COVID-19 in 2020, the analysis of activities and travel behavior of urban residents is the key for the prevention and control of epidemic situation. Based on this, the research on track data mining and semantic location perception is conducted. The analysis of travel behavior characteristics of urban residents is helpful to carry out epidemic prevention activities scientifically. However, the traditional manual survey and statistical analysis cannot meet the needs of the rapid development of urbanization. On the other hand, with the application and development of information technology such as communication, location and storage, a …large number of mobile trajectory data of urban residents can be collected and stored. These trajectory data contain rich spatiotemporal semantic information. Through mining and analysis, a lot of valuable travel information can be get and then the daily behavior of individual users and the spatial distribution characteristics of group users’ movement can be found. The results can effectively serve the current epidemic prevention work and can be applied to the infection tracking in the process of epidemic prevention. Show more

Keywords: Track data mining, semantic location awareness, COVID-19, prevention and control system

DOI: 10.3233/JIFS-189295

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Alberto Morales-Rosales, Luis | Algredo-Badillo, Ignacio | Lobato-Baez, Mariana | Hernández-Gracidas, Carlos | Rodríguez-Rangel, Héctor

Article Type: Research Article

Abstract: In this research, we implement an intelligent quantitative model to assess a specific qualitative intelligence scale in children between 5 and 8 years old, based on augmented reality and the well known WISC-IV test. The output of the model is a cognitive factor associated with the analogical reasoning level of the child, and the ulterior analysis of the evaluation measure is intended to serve as an aid for the teacher to discover problems related to the child’s ability to solve visual analogies. A quantitative approach to assess analogical reasoning is suitable to avoid ambiguous evaluations of qualitative results. Also, given …that the assessment employs a visual WISC subtest, it constitutes a non-verbal evaluation. Finally, the fact that the model is based on an intelligent approach guarantees that the assessment process is impartial, based on the quantitative scores obtained, instead of an interpretation of the results. The purpose of this work is to give evidence that a computer-aided adaption, employing augmented reality and a Fuzzy Petri Net, for the WISC test, will improve the teaching-learning process in children ranges from 5 to 8 years old. A case study is analyzed, where both the paper-based and the augmented reality versions are applied to five children with Spanish as their native tongue. We show the feasibility and potentiality of implementing the test in a multimedia version to provide teachers with a more reliable resource for the diagnosis and treatment of possible learning deficiencies in the child regarding disambiguation, non-verbality, and impartiality. Show more

Keywords: Intelligent quantitative model, analogical reasoning, WISC-IV test, augmented reality learning environment, computer-aided assessments

DOI: 10.3233/JIFS-200588

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2020

Authors: Liu, Qi | Huang, Zhenzhen

Article Type: Research Article

Abstract: Since December 2019, the outbreak of novel coronavirus pneumonia has brought great challenges to global public health, which is the most serious epidemic over the past hundred years. The urban rail transit is an important part of public transport in large cities with characteristic of intensive passengers and confined space, which is easy to become viral infection intermediary. In order to prevent and control the situation of the epidemic, the police’s public security department for urban rail transit and the urban rail transit operation company have established a three-layer filter network, which is composed of safety inspection, patrol and temporary …interrogation, and intelligent police service, and this network implements the deep learning technology to identify key persons, prohibited luggage, and the body temperature of passengers. For the problem of uncertainty in total passenger flow and its density, this paper proposes a method for re-establishing the passenger flow model to focus on data monitoring, and resetting the threshold value of alarm to control the passenger density. In view of the difficulty of passenger identification caused by mask during the epidemic, this paper proposes a systematic schema of timely adjusting face recognition algorithm, modifying the alarm threshold, using iris recognition system, carrying out information collision comparison, deep mining and intelligent judging, which discover the high-risk groups of epidemic prevention and control in time. China’s police’s public security department for urban rail transit aims at prevention of virus input, infection, riot, fake new, scientific prevention and control, and has made precise policy implementation to hold urban rail transit’s covid-19 intelligent prevention and control work, finally won the battle and effectively guaranteed the people’s life safety and health. Show more

Keywords: COVID-19, epidemic prevention and control, urban rail transit, intelligent police, big data, deep learning

DOI: 10.3233/JIFS-189307

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2020

Authors: Zheng, Bing | Zhang, Xiaoying | Yun, Daweia

Article Type: Research Article

Abstract: By comparing several cloud computing of big data network center during COVID-19, this paper proposes a new topology model, which realizes two functions of cloud computing big data center caching and big data real-time distribution. In addition, cloud computing network requires higher performance than traditional application big data center, which makes the consideration of network platform construction performance different from the traditional understanding. During COVID-19, we deeply understood the underlying attributes of cloud, combined with the topology model, we can realize the decoupling of cloud computing big data system, change the situation of direct connection between upstream and downstream, and …have more reliable and efficient transmission of message and command big data. Show more

Keywords: Measurement and control system, cloud computing, central cache, real time big data distribution

DOI: 10.3233/JIFS-189289

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Wang, Lilin

Article Type: Research Article

Abstract: The light steel structure is always the common material of the movable plank house, and the new bud light steel system is the light steel system used for a long time after the earthquake. This paper discusses the mechanical system of the light steel structure of Huoshenshan hospital, which was built in ten days. In the process of building, the geometric form of roof stress has changed. In the actual structural design, the designer seldom takes the calculation of construction load into account, which is quite different from the actual construction process. So it is very important to simulate and …monitor the whole process of structure installation. In this paper, the finite element software MIDAS / Gen is used for simulation analysis to ensure that the simulation analysis results are consistent with the construction process, the model material and the actual size are completely consistent, and the stress simulated by the software can meet the needs of the actual stress through the actual measurement. Show more

Keywords: New bud light steel system, light steel frame, geometric evolution, prefabricated house

DOI: 10.3233/JIFS-189300

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Wang, Jin

Article Type: Research Article

Abstract: Facing COVID-19 epidemic, many countries have recently strengthened epidemic prevention and control measures. The reliability of safety management is of great significance to personnel management and control during the COVID-19 epidemic period. The focus of security management of early warning is to monitor and identify the moving target. The current optical flow method is vulnerable to the influence of light changes and background movement, and it is not very accurate for moving target detection in dynamic complex background. In this paper, aiming at the traditional Lucas Kanade optical flow method, the inter frame difference method, mean shift clustering algorithm and …morphological processing are combined to optimize and improve on the original basis, so that the moving target detection effect in both simple and complex environments is significantly improved. At the same time, the improved algorithm also reduces the execution time to a certain extent, and has a certain resistance to noise interference such as light changes. This has a certain ability test value for personnel control during the epidemic. Show more

Keywords: Lucas Kanade optical flow method, COVID-19, mean shift algorithm, security management, moving target

DOI: 10.3233/JIFS-189293

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Guo, Xingru | Liu, Aijun | Li, Xia | Liu, Taoning

Article Type: Research Article

Abstract: Rh-negative rare blood inventory protection plays an important role in emergency blood protection. Normally, hospitals typically hold a fixed amount of daily reserve in response to emergency needs, but the measure can increase the unnecessary cost of repeated freezing and thawing. In order to save manpower, protect blood resources and reduce costs, a two-stage stochastic model is proposed to determine the optimal daily reserve of Rh-negative red blood cells, taking into account the uncertainty of demand. First, the model focuses on minimizing operational cost, shortage cost and damage caused by blood substitution. Then, the proposed model generates a series of …discrete scenarios to solve the uncertainty of demand and predict the demand. In addition, a case study is presented to prove the validity of the proposed model with real data. Sensitivity analysis is also established to observe the effect of parameter changes on the results. Finally, the results show that the proposed model can effectively reduce the cost and current waste. Show more

Keywords: Rh-negative, red blood cells, inventory management, stochastic demand, two-stage stochastic model

DOI: 10.3233/JIFS-192182

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2020

Authors: Xu, Hesheng

Article Type: Research Article

Abstract: University legal education is of great significance to the personal development and social stability of college students. At present, there are certain problems in the traditional teaching system, which has led to inefficient university legal education. In order to improve the legal teaching effect of the university, based on machine learning and neural networks, this paper integrates and optimizes the original hardware and software and operation process, and further highlights the functions of interconnection and sharing, automatic sensing, real-time recording, interactive feedback, dynamic supervision, and intelligent analysis, which greatly facilitates the evaluation of teaching at all levels. In particular, this …study uses big data technology to conduct an intelligent analysis of data completeness, multimedia application rate, system execution, and average test scores, and scientifically evaluates the implementation of basic-level education systems and the effectiveness of education, which can effectively solve the problems of quantitative formalization and qualitative subjectivity of current education evaluation from a technical level. In addition, this study designs a control experiment to analyze the system performance. The research results show that the model proposed in this paper has a certain effect. Show more

Keywords: Machine learning, neural network, university law, education system

DOI: 10.3233/JIFS-189311

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Siddique, Saba | Ahmad, Uzma | us Salam, Wardat | Akram, Muhammad | Smarandache, Florentin

Article Type: Research Article

Abstract: The concept of generalized complex neutrosophic graph of type 1 is an extended approach of generalized neutrosophic graph of type 1. It is an effective model to handle inconsistent information of periodic nature. In this research article, we discuss certain notions, including isomorphism, competition graph, minimal graph and competition number corresponding to generalized complex neutrosophic graphs. Further, we describe these concepts by several examples and present some of their properties. Moreover, we analyze that a competition graph corresponding to a generalized complex neutrosophic graph can be represented by an adjacency matrix with suitable real life examples. Also, we enumerate the …utility of generalized complex neutrosophic competition graphs for computing the strength of competition between the objects. Finally, we highlight the significance of our proposed model by comparative analysis with the already existing models. Show more

Keywords: Isomorphism, competition graphs of type 1, minimal graphs, competition matrix, comparative analysis

DOI: 10.3233/JIFS-201338

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2020

Authors: Meena, V. | Gireesha, Obulaporam | Krithivasan, Kannan | Shankar Sriram, V.S.

Article Type: Research Article

Abstract: Mobile Cloud Computing (MCC)’s rapid technological advancements facilitate various computational-intensive applications on smart mobile devices. However, such applications are constrained by limited processing power, energy consumption, and storage capacity of smart mobile devices. To mitigate these issues, computational offloading is found to be the one of the promising techniques as it offloads the execution of computation-intensive applications to cloud resources. In addition, various kinds of cloud services and resourceful servers are available to offload computationally intensive tasks. However, their processing speeds, access delays, computation capability, residual memory and service charges are different which retards their usage, as it becomes time-consuming …and ambiguous for making decisions. To address the aforementioned issues, this paper presents a Fuzzy Simplified Swarm Optimization based cloud Computational Offloading (FSSOCO) algorithm to achieve optimum multisite offloading. Fuzzy logic and simplified swarm optimization are employed for the identification of high powerful nodes and task decomposition respectively. The overall performance of FSSOCO is validated using the Specjvm benchmark suite and compared with the state-of-the-art offloading techniques in terms of the weighted total cost, energy consumption, and processing time. Show more

Keywords: Computational offloading, fuzzy logic, mobile cloud computing, multisite offloading, swarm optimization

DOI: 10.3233/JIFS-189148

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Shan, Xianming | Liu, Huixin | Pan, Qinghong

Article Type: Research Article

Abstract: Due to the strict personnel control measures in COVID-19 epidemic, the control system cannot be maintained and managed manually. This puts forward higher requirements for the accuracy of its fault-tolerant performance. The control system plays an increasingly important role in the rapid development of industrial production. When the sensor in the system fails, the system will become unstable. Therefore, it is necessary to accurately and quickly diagnose the faults of the system sensors and maintain the system in time. This paper takes the control system as the object to carry out the fault diagnosis and fault-tolerant control research of its …sensors. A network model of wavelet neural network is proposed, and an improved genetic algorithm is used to optimize the weights and thresholds of the neural network model to avoid the deficiencies of traditional neural network algorithms. For the depth sensor of a certain system, an online fault diagnosis scheme based on RBF (Radial Basis Function) neural network and genetic algorithm optimized neural network was designed. The disturbance fault, “stuck” fault, drift fault and oscillation fault of the depth sensor are simulated. Simulation experiments show that both online fault diagnosis schemes can accurately identify sensor faults and the genetic algorithm optimized neural network is superior to RBF neural network in both recognition accuracy and training time under the influence of COVID-19. Show more

Keywords: Fault diagnosis, COVID-19, fault-tolerant control, neural network, genetic algorithm optimization

DOI: 10.3233/JIFS-189306

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Li, Meng | Zhao, Yifei | Xiong, Xinglong | Ma, Yuzhao

Article Type: Research Article

Abstract: Synchronous delivery with different vehicles, as an emerging concept of the delivery network, improves the efficiency of the modern logistics system significantly, which gradually gives birth to a new issue: the traveling salesman problem with drone (TSP-D). In this paper, we propose a one-truck-multiple-drone (OTMD) model on the base of the TSP-D. Compared with the traditional one-truck-one-drone (OTOD) and multiple drones models, our scheme introduces a united objective function into the optimization calculation. In terms of the proposed multiple levels iterative theory, we can compute the optimal synchronous delivery network that takes both the total delivery time and the number …of drones into consideration. Four types of customer distributions are employed to investigate the OTMD model and its associated calculation approaches. Comparing the parameters of the optimal network in different delivery models, we study the relationship among the total delivery time, customer distribution and the number of serving drones. These simulation results verify the feasibility and practicality of the OTMD, and demonstrate the features of optimization calculation with different customer distributions, being beneficial to improve the efficiency of the model logistics system. Show more

Keywords: Traveling salesman problem with drone (TSP-D), one-truck-multiple-drone (OTMD) model, optimization calculation, modern logistics system

DOI: 10.3233/JIFS-200818

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2020

Authors: Guo, Jingni | Xu, Junxiang | Liao, Wei

Article Type: Research Article

Abstract: The multimodal transport network in the region with complex environment and being easily affected by disturbance factors is used as the research object in our work. The characteristics of the cascading failure of such multimodal transport network were analyzed. From the perspective of network load redistribution, the risk control methods for the cascading failure of the multimodal transport network were investigated. This research aims to solve the problem that traditional load redistribution methods usually ignore the original-destination (OD) constraint and uncertain risks. The conditional value-at-risk (CVaR) was improved based on the Bureau of Public Roads (BPR) road impedance function to …quantify the uncertainty of the disturbance factors. A nonlinear programming model was established with the generalized travel time as the objective function. A parallelly-running cellular ant colony algorithm was designed to solve the model. Empirical analysis was conducted on the multimodal transport network in Sichuan-Tibet region of China. The results of the empirical analysis verified the applicability of the proposed load redistribution method to such kind of regions and the effectiveness of the algorithm. This research provides theoretical basis and practical reference for the risk control of the cascading failure of multimodal transport networks in some regions. Show more

Keywords: Uncertain disturbance, multimodal transport network, risk control, load redistribution, cellular ant colony algorithm

DOI: 10.3233/JIFS-200968

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Liu, Haichao | Jin, Xiangjie | Zhang, Fagui

Article Type: Research Article

Abstract: With the continuous spread of COVID-19 epidemic, the strict control of personnel makes it a problem to optimize the design of vehicle parameters after field measurement. The energy absorption characteristics and deformation mode of the front structure of the vehicle determine the acceleration or force response of the vehicle body during the impact, which plays an important role in occupant protection. The traditional multi-objective optimization method is to transform multi-objective problems into single objective optimization problems through weighted combination, objective planning, efficiency coefficient and other methods. This method requires a strong prior knowledge. The purpose of this paper is to …combine the experimental design with the Multi-objective Particle Swarm Optimization (MPSO) method to achieve the optimization of the crash worthiness of automobile structure. This method can effectively overcome the defect of low precision caused by the conventional response surface method in the whole design space. In this paper, the multi-objective particle swarm optimization method is applied to the research of Crash worthiness optimization of automobile structure, which expands the application field of the multi-objective particle swarm optimization method, and also has a very big role in the optimization of other complex systems. It can be seen from the experiment that the speed of multi-objective particle swarm optimization is much faster than that of other methods. Only 100 iterations can get the relative better results. The case study on the front structure of a car shows that the method has a good result. It is of great significance to apply the method to the optimization design of the crash worthiness of the car structure to improve the crash safety of the car under the influence of COVID-19 epidemic. Show more

Keywords: Energy absorption, COVID-19, multi-objective optimization, particle swarm optimization, crash safety

DOI: 10.3233/JIFS-189305

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Zhao, Gaoli | Song, Junping

Article Type: Research Article

Abstract: To build a network security system combining active defense and passive defense during covid-19, we need to break the original Castle type passive defense concept and build a reliable, controllable, flexible and active network environment to find defense points. The key is that the system should be able to actively predict and control our defenses. Any scheme cannot achieve absolute safety, only to minimize the probability of safety accidents, through various measures to assess and predict the possible points of safety accidents, and actively prevent the occurrence of accidents. In the management and construction of network security, we should realize …that network security management is a comprehensive system engineering. We should start from the three aspects of strategy, management and technology, and build a more effective and reliable network security system on the basis of traditional passive defense and active defense technology, which can better maintain big data security during covid-19. Show more

Keywords: Network security model, active defense technology, active passive defense, network security system

DOI: 10.3233/JIFS-189287

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Hu, Yun | Li, Ning | Luo, Chenyang

Article Type: Research Article

Abstract: During the COVID-19 epidemic, college students could not return to the school, which had a great impact on the talent training of colleges and universities. Based on the statistical learning theory, this paper puts forward an evaluation model for the cultivation of innovative talents in universities after the epidemic. In this paper, the evaluation index system of the quality of innovative and entrepreneurial personnel training in Universities, which is composed of four first-class indexes: environment, teaching links, teachers and students, is constructed. At the same time, this paper uses the fuzzy comprehensive evaluation method for empirical research. Firstly, the factor …set of the evaluation object and the grade domain of the comprehensive evaluation are determined. Then, AHP is used to determine the weight of evaluation indexes and expert scoring method is used to determine the single factor fuzzy comprehensive evaluation matrix of each level. According to the evaluation matrix, the fuzzy relation between evaluation object and evaluation set is calculated. Finally, according to the principle of maximum membership degree, the evaluation grade corresponding to the maximum value in the fuzzy relation set is calculated as the evaluation result of the final evaluation object. The empirical results show that this method can improve the accuracy of the evaluation model of innovation and entrepreneurship talent training, and has a certain reference value for the talent training in Universities. Show more

Keywords: Fuzzy set, statistical learning theory, single factor fuzzy comprehensive evaluation matrix, talent training

DOI: 10.3233/JIFS-189303

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2020

Authors: Chen, Xi

Article Type: Research Article

Abstract: During the COVID-19 pandemic, the maintenance of the wind turbine is unable to be processed due to the problem of personnel. This paper presents two neural network models: BP neural network and LSTM neural network combined with Particle Swarm Optimization (PSO) algorithm to realize obstacle maintenance detection for wind turbine. Aiming at the problem of gradient vanishing existing in the traditional regression neural network, a fault diagnosis model of wind turbine rolling bearing is proposed by using long-term and short-term memory neural network. Through the analysis of an example, it is verified that the diagnosis results of this method are …consistent with the actual fault diagnosis results of wind turbine rolling bearing and the diagnosis accuracy is high. The results show that the proposed method can effectively diagnose the rolling bearing of wind turbine, and the long-term and short-term memory neural network still has good fault diagnosis performance when the difference of fault characteristics is not obvious, which shows the feasibility and effectiveness of the method. Show more

Keywords: Wind turbine, fault diagnosis, particle swarm optimization algorithm, BP neural network

DOI: 10.3233/JIFS-189301

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Han, Lu | Su, Zhi | Lin, Jing

Article Type: Research Article

Abstract: Ever increasing ordinal variables are being collected by the Personal Credit Reference System in China, however this system suffers from analysis of this kind of data, which cannot be calculated by Euclidean distance. In this study, we put forward a hybrid KNN algorithm based on Sugeno measure, and we prove that the error of this algorithm is smaller than that of Euclidean distance, furthermore, we use real data obtained from the Personal Credit Reference System to perform experiments and get the user’s initial portrait. Through the comparisons with Kmeans algorithm and other different distance measures in KNN algorithm, we find …that the hybrid KNN algorithm is more suitable for clustering personal credit data. Show more

Keywords: Hybrid KNN clustering, personal credit reference system, Sugeno measure, user’s portrait

DOI: 10.3233/JIFS-200191

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Bu, Suhua

Article Type: Research Article

Abstract: In the era of the Internet of Things, smart logistics has become an important means to improve people’s life rhythm and quality of life. At present, some problems in logistics engineering have caused logistics efficiency to fail to meet people’s expected goals. Based on this, this paper proposes a logistics engineering optimization system based on machine learning and artificial intelligence technology. Moreover, based on the classifier chain and the combined classifier chain, this paper proposes an improved multi-label chain learning method for high-dimensional data. In addition, this study combines the actual needs of logistics transportation and the constraints of the …logistics transportation process to use multi-objective optimization to optimize logistics engineering and output the optimal solution through an artificial intelligence model. In order to verify the effectiveness of the model, the performance of the method proposed in this paper is verified by designing a control experiment. The research results show that the logistics engineering optimization based on machine learning and artificial intelligence technology proposed in this paper has a certain practical effect. Show more

Keywords: Machine learning, artificial intelligence, logistics, optimization

DOI: 10.3233/JIFS-189244

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Shi, Junyan | Jiang, Han

Article Type: Research Article

Abstract: Under the influence of COVID-19, detection and identification of moving targets are very important for personnel management. A lot of research work has improved the accuracy and robustness of the moving target tracking method, but the recognition accuracy of the traditional target tracking method in complex scenes (lighting changes, background interference, posture changes and other factors) is not satisfactory. In this paper, in view of the limitations of single feature representation of target objects, the method of fusion of HSV color features and edge direction features is used to identify and detect moving targets. In each frame of the tracking …process, the weight of each feature is adjusted adaptively according to the proposed fusion strategy, and the position of the target is located by using the method of double template matching. Experiments show that the proposed tracking algorithm based on multi feature fusion can meet the requirements of moving target recognition in complex scenes. The method proposed in this paper has a certain reference value for personnel management under the influence of COVID-19. Show more

Keywords: Moving targets, detection and identification, HSV color feature, edge direction

DOI: 10.3233/JIFS-189302

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Niu, Meng

Article Type: Research Article

Abstract: The COVID-19 epidemic has brought a huge impact to the clothing industry. Because of the inconveniences caused by countermeasures, clothing consumers can’t go to physical stores to try on, so it is urgent to develop a virtual clothing trial system. In addition, online fitting and online shopping gradually become the trend of clothing consumption. Based on virtual reality technology, this paper proposes a virtual clothing fitting system, and studies the color saturation in the process. In this paper, a method of parametric drawing of garment characteristic curve is proposed, and the shape of garment is designed by using control vertices. …Based on this, this paper presents four forms of sutured parabola space and their control point solving algorithm. According to the principle of scale method, a three-dimensional coordinate transformation model of feature points is established. The model can calculate the coordinates of each characteristic value point of clothing according to the body shape information provided by customers and the empirical formula of different clothing styles, and then reverse calculate the curve control point. Furthermore, Bezier surface generation method is used to fit the control points. After the surface patches are spliced, the 3D rigid clothing model can be obtained. Experiments show that the method of personalized clothing modeling in this paper is efficient and accurate, which can be further extended to the observation system with larger degree of freedom. Show more

Keywords: Virtual fitting, color saturation, stitching parabola, Bezier surface generation, garment modeling.

DOI: 10.3233/JIFS-189292

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Yan, Hao

Article Type: Research Article

Abstract: Under the influence of epidemic situation, the treatment of pollutants is stricter. After the epidemic, how to treat the river pollutants by microorganisms has become a difficult problem. In this paper, the microbial treatment technology of water pollution was studied, and the water quality model was used to simulate the process of microbial degradation of river pollutants. The dynamic equation is used to describe the relationship among microbial proliferation, removal of organic pollutants, change of dissolved oxygen concentration, different forms of nitrogen and different forms of phosphorus, so as to realize the mathematical expression of water quality change in the …process of microbial treatment of river pollutants. Finally, the numerical simulation model of microbial treatment of river pollution is obtained through experimental analysis, which provides an accurate reference model for the prevention and control of river pollution after the outbreak. Show more

Keywords: Water pollution, microbial treatment, water quality model, microbial degradation, river pollution

DOI: 10.3233/JIFS-189291

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2020

Authors: Li, Jiwei

Article Type: Research Article

Abstract: Under the influence of novel corona virus pneumonia epidemic prevention and control, it has put forward higher requirements for data storage and processing for personnel management system. The distributed asynchronous data aided computer information interaction system can solve the problem of multi node concurrent data processing. The traditional computer information interaction system has poor real-time performance, low precision and asynchronous data processing ability. The invocation features of message queuing asynchronous caching mode are combined with the standardization of Web services and cross language with cross platform access features in this paper. Through the combination of the two technologies, a flexible …and universal asynchronous interaction architecture of distributed system is established. Based on Web service technology and system to system access, the call and response of tasks between modules are carried out in the system, which makes the interaction between the whole system have the characteristics of message driven. The test result shows that the system proposed in this paper has good real-time performance and strong data processing ability. It is suitable for the data interaction of distributed personal management system under the influence of novel corona virus pneumonia epidemic prevention and control. Show more

Keywords: Web service, distributed asynchronous data, epidemic prevention and control, personal management system

DOI: 10.3233/JIFS-189299

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Wang, Wensheng | Han, Yu | Gao, Qing | Hu, Muhan

Article Type: Research Article

Abstract: This paper uses statistical learning theory and big data analysis to study the energy consumption structure of China from qualitative and quantitative aspects during COVID-19. According to the domestic and foreign scholars’ research on the optimization of energy consumption structure, the carbon emission factor is considered in the optimization of energy consumption structure. Taking the minimum energy consumption cost and carbon dioxide emission as the objective function, the carbon dioxide emission is taken as the objective function, and the total energy consumption and various energy consumption proportions as the constraint conditions, the multi-objective planning method is used to evaluate the …energy consumption structure of China. The optimization model of source consumption structure is analyzed, and the medium and long-term energy transformation path and optimization model under low-carbon constraints are studied. Combined with the experimental algorithms related to big data, it is concluded that China’s economic development mainly depends on a large amount of energy consumption during the COVID-19 period. On this basis, some suggestions are put forward to realize the sustainable development of China’s economy and energy. Show more

Keywords: Statistical learning theory, low carbon constraint, transformation path, optimization model

DOI: 10.3233/JIFS-189304

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Wang, Zhenpeng

Article Type: Research Article

Abstract: In the era of big data transformation, with the emergence of COVID-19, tourism has been given more social responsibilities. Tourism construction in the Yellow River Basin is an indispensable part of tourism construction in China. This paper analyzes the existing eco-tourism resources in Kaifeng City and Shandong Province, as well as the necessity and construction conditions of developing tourism. In this paper, principal component analysis is used to analyze the resource conditions, regional conditions and environmental conditions of the Yellow River tourism resources. The comprehensive evaluation model and index system of tourism resources are constructed. Big data transformation has been …realized. The purpose of this paper is to clarify the current situation and potential of tourism in the Yellow River Basin, and to provide reference for the development of tourism in the Yellow River Basin during COVID-19. Show more

Keywords: PCA, tourist resources, yellow river basin, comprehensive evaluation

DOI: 10.3233/JIFS-189288

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Dafei, Wu, | Qinghong, Pan,

Article Type: Research Article

Abstract: In order to strengthen the management and control of personnel flow and the timeliness of information dissemination during the COVID-19 epidemic, it is necessary to improve the reliability of authority and content management. The extensive application of authority information management can closely connect the professional system with the production activities of enterprises. At present, the traditional authority management level is complex, and the management of complex data is chaotic. This paper is based on ASP.NET. This paper proposes a data authority management method. The main function of this method is to establish a standard three-tier structure of rights management level …by using the open-source string template engine technology, tag analysis, SEO search engine optimization technology and information collection technology. This method provides a general process oriented and automatic management platform for users through the hierarchical management mechanism. This technology can meet people’s rights and content requirements for creating, publishing and updating websites without understanding the technology itself. The experimental results show that the rapid management mechanism based on authority management can accurately handle and manage authority and data which can improve the accuracy and timeliness of personnel flow control under the impact of the COVID-19 epidemic. Show more

Keywords: ASP.NET, permission management system, COVID-19 epidemic, string template, hierarchical management mechanism

DOI: 10.3233/JIFS-189283

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Wang, Bin | Zhou, Qingyuan

Article Type: Research Article

Abstract: The global economy appears the trend of anti-globalization under the influence of COVID-19. Based on the input-output table of lead database from 2006 to 2020, this paper divides the factors that affect the development of financial industry in China, the United States and Russia into six aspects: price, intermediate input, household consumption, government consumption, export and import. ADGA-BP neural network model is proposed in this paper, which is based on six aspects of price, intermediate input, consumer, government consumption, export and import. The intermediate input is decomposed from the perspective of industrial structure to study the interrelationship between financial industry …and other industries in the three countries. The results show that the intermediate input is the main factor in the development of financial industry in the three countries, but the source industries of the intermediate input are not the same; the two factors of household consumption and price are closely related to the development of financial industry in the three countries, and they all play a role in promoting China, while the relationship between household consumption and the United States and between price and Russia is reverse; Government consumption only has a significant impact on Russia; from the perspective of mutual influence, the mutual investment between the financial industry of China and the United States is relatively large, while the relationship between the Russian financial industry and the two countries is relatively weak. It shows that under the background of covid-19, the development of financial industry is affected. Show more

Keywords: Adaptive genetic algorithm, BP neural network, COVID-19, financial industry

DOI: 10.3233/JIFS-189280

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Fengwei, Ai, | Nan, Wang,

Article Type: Research Article

Abstract: At present, the normal teaching is seriously disturbed by the epidemic situation. In order to ensure the smooth progress of teaching, online teaching is a necessary way. Based on the current situation, this paper discusses the integration of urban and rural planning and human geography teaching in university courses. Based on the full analysis of the advantages of the original curriculum, this paper adjusts the curriculum of urban and rural planning and human geography. The new system focuses on the characteristics of “broad foundation and clear main line”, and follows the three main lines of “art, design and geography” to …optimize the design. A questionnaire survey was conducted among 200 online students in our school and the data were processed by multidimensional BP neural network analysis. The experimental results show that the method proposed in this paper can improve the efficiency of online teaching. Show more

Keywords: Epidemic situation, urban and rural planning and human geography, teaching integration, Information method of online education

DOI: 10.3233/JIFS-189282

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Yingzhi, Xu | Lu, Yun

Article Type: Research Article

Abstract: Under the influence of novel coronavirus pneumonia, the traditional manual oil painting creation has put forward higher requirements. The disadvantages of traditional hand drawing are very obvious: tedious, inconvenient to modify and save, slow speed of painting, which can no longer meet the requirements of social development. In this paper, the fitness of oil painting function is discussed. Through the analysis of the experimental results, it is found that this method has important reference value for optimizing algorithm and improving traditional hand drawing during COVID-19.

Keywords: Genetic algorithm, aesthetic criteria, COVID-19, genetic operator, fitness function

DOI: 10.3233/JIFS-189265

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Yang, Shuang

Article Type: Research Article

Abstract: Under the influence of the COVID-19 epidemic situation, many countries have taken many measures to control the flow of people. The inability of people to gather makes art color measurement a problem. Color matching and coordination and color space conversion have always been the research focus of art color measurement. This paper studies a method of fuzzy intelligent reasoning in art color measurement. Based on case-based reasoning and rule-based reasoning, this method is an important self-learning and self-maintenance method in the field of artificial intelligence and expert system. On the basis of expounding the basic characteristics of color and color …space, this paper designs the process principle of case-based reasoning and the process of rule-based reasoning. In this paper, case and rule knowledge representation method, case retrieval technology and rule conflict resolution strategy are established. Based on the above strategy, the color case base is established. In addition, the rule table is established by combining color-brewer with rule reasoning and referring to color-brewer. The rule table has a certain reference value for the application of intelligent reasoning method in the field of art color measurement under the influence of COVID-19 epidemic. Show more

Keywords: Color-brewer, COVID-19 epidemic, rule-based reasoning, self-learning, color measurement

DOI: 10.3233/JIFS-189286

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Ali, Mohamed R. | Hadhoud, Adel R. | Ma, Wen-Xiu

Article Type: Research Article

Abstract: In this approximation study, a nonlinear singular periodic model in nuclear physics is solved by using Hermite wavelets technique (HW) coupled with numerical iteration technique such as Newton Raphson (NR) for solving the resulting nonlinear system. The stimulation of offering this numerical work comes from the aim of introducing a consistent framework that has the effective structures of Hermite with the wavelets. Two numerical examples of the singular periodic model in nuclear physics have been investigated to observe the robustness, proficiency, and stability of the designed scheme. The proposed outcomes of HW technique are compared from available numerical solutions that …established fitness of the designed procedure through performance evaluates on a multiple execution. Show more

Keywords: Singular periodic systems in nuclear physics, Hermite wavelets, hybrid approach, Gaussian formula of integration, collocation technique

DOI: 10.3233/JIFS-201045

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Jiafeng, Li, | Hui, Hu, | Xiang, Li, | Qian, Jin, | Tianhao, Huang,

Article Type: Research Article

Abstract: Under the influence of COVID-19, the economic benefits of shale gas development are greatly affected. With the large-scale development and utilization of shale gas in China, it is increasingly important to assess the economic impact of shale gas development. Therefore, this paper proposes a method for predicting the production of shale gas reservoirs, and uses back propagation (BP) neural network to nonlinearly fit reservoir reconstruction data to obtain shale gas well production forecasting models. Experiments show that compared with the traditional BP neural network, the proposed method can effectively improve the accuracy and stability of the prediction. There is a …nonlinear correlation between reservoir reconstruction data and gas well production, which does not apply to traditional linear prediction methods Show more

Keywords: Back propagation neural network, shale gas exploitation, economic benefit, COVID-19

DOI: 10.3233/JIFS-189279

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Hongwei, Zhu, | Xuesong, Wang,

Article Type: Research Article

Abstract: With the continuous progress of social science and technology, the development of the Internet of things is growing. With the development of Internet of things, security problems emerge in endlessly. During the period of COVID-19, the Internet of Things have been widely used to fight virus outbreak. However, the most serious security problem of the Internet of things is network intrusion. This paper proposes a balanced quadratic support vector machine information security analysis method for Internet of things. Compared with the traditional support vector machine Internet of things security analysis method, this method has a higher accuracy, and can shorten …the detection time, with efficient and powerful characteristics. The method proposed in this paper has certain reference value to the Internet of things network intrusion problem. It provides better security for the Internet of things during the protection period of covid-19. Show more

Keywords: SVM, Balanced binary decision, internet of things security, intrusion detection, COVID-19

DOI: 10.3233/JIFS-189259

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Abdulhay, Enas | Alafeef, Maha | Hadoush, Hikmat | Arunkumar, N.

Article Type: Research Article

Abstract: Autism is a developmental disorder that influences social communication skills. It is currently diagnosed only by behavioral assessment. The assessment is susceptible to the experience of the examiner as well as to the descriptive scaling standard. This paper presents a computer aided approach to discrimination between neuro-typical and autistic children. A new method- based on the computing of the elliptic area of the Continuous Wavelet Transform complex plot of resting state EEG- is presented. First, the complex values of CWT, as a function of both time and frequency, are calculated for every EEG channel. Second, the CWT complex plot is …obtained by plotting the real parts of the resulted CWT values versus the related imaginary components. Third, the 95% confidence value of the elliptic area of the complex plot is computed for every channel for both autistic and healthy subjects; and the obtained values are considered as the first set of features. Fourth, three additional features are computed for every channel: the average CWT, the maximum EEG amplitude, and the maximum real part of CWT. The classification of those features is realized through artificial neural network (ANN). The obtained accuracy, sensitivity and specificity values are: 95.9%, 96.7%, and 95.1% respectively. Show more

Keywords: Autism, EEG, CWT, Elliptic area, classification

DOI: 10.3233/JIFS-189176

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Yongjun, Tang

Article Type: Research Article

Abstract: During the period of COVID-19 protection, Internet of Things (IoT) has been widely used to fight the outbreak of pandemic. However, the security is a major issue of IoT. In this research, a new algorithm knn-bp is proposed by combining BP neural network and KNN. Knn-bp algorithm first predicts the collected sensor data. After the forecast is completed, the results are filtered. Compared with the data screened by traditional BP neural network, k-nearest-neighbor algorithm has good data stability in adjusting and supplementing outliers, and improves the accuracy of prediction model. This method has the advantages of high efficiency and small …mean square error. The application of this method has certain reference value. Knn-bp algorithm greatly improves the accuracy and efficiency of the Internet of things. Internet of things network security is guaranteed. It plays an indelible role in the protection of COVID-19. Show more

Keywords: Artificial neural network, security design, internet of things, KNN, COVID-19

DOI: 10.3233/JIFS-189266

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Kai, Cui

Article Type: Research Article

Abstract: Under the influence of COVID-19, an efficient Ad-hoc network routing algorithm is required in the process of epidemic prevention and control. Artificial neural network has become an effective method to solve large-scale optimization problems. It has been proved that the appropriate neural network can get the exact solution of the problem in real time. Based on the continuous Hopfield neural network (CHNN), this paper focuses on the study of the best algorithm path for QoS routing in Ad-hoc networks. In this paper, a new Hopfield neural network model is proposed to solve the minimum cost problem in Ad-hoc networks with …time delay. In the improved version of the path algorithm, the relationship between the parameters of the energy function is provided, and it is proved that the feasible solution of the network belongs to the category of progressive stability by properly selecting the parameters. The calculation example shows that the solution is not affected by the initial value, and the global optimal solution can always be obtained. The algorithm is very effective in the prevention and control in COVID-19 epidemic. Show more

Keywords: Ad-hoc Network, Routing Algorithm, Neural Network, COVID-19

DOI: 10.3233/JIFS-189273

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Sengan, Sudhakar | Priya, V. | Syed Musthafa, A. | Ravi, Logesh | Palani, Saravanan | Subramaniyaswamy, V.

Article Type: Research Article

Abstract: Breast cancer should be diagnosed as early as possible. A new approach of the diagnosis using deep learning for breast cancer and the particular process using segmentation strategies presented in this article. Medical imagery is an essential tool used for both diagnosis and treatment in many fields of medical applications. But, it takes specially trained medical specialists to read medical images and make diagnoses or treatment decisions. New practices of interpreting medical images are labour exhaustive, time-wasting, expensive, and prone to error. Using a computer-aided program which can render diagnosis and treatment decisions automatically would be more beneficial. A new …computer-based detection method for the classification between compassionate and malignant mass tumours in mammography images of the breast proposed. (a) We planned to determine how to use the challenging definition, which produces severe examples that boost the segmentation of mammograms. (b) Employing well designing multi-instance learning through deep learning, we validated employing inadequately labelled data of breast cancer diagnosis using a mammogram. (c) The study is going through the Deep Lung method incorporating deep multi-dimensional automated identification and classification of the lung nodule. (d) By combining a probabilistic graphic model in deep learning, it authorizes how weakly labelled data can be used to improve the existing breast cancer identification method. This automated system involves manually defining the Region Of Interest (ROI), with the region and threshold values based on the next region. The High-Resolution Multi-View Deep Convolutional Neural Network (HRMP-DCNN) mainly developed for the extraction of function. The findings collected through the subsequent in available public databases like mammography screening information database and DDSM Curated Breast Imaging Subset. Ultimately, we’ll show the VGG that’s thousands of times quicker, and it is more reliable than earlier programmed anatomy segmentation. Show more

Keywords: Deep convolutional neural network, computer-based automated detection, breast cancer screening, deep learning, machine learning, mammography, fuzzy logic.

DOI: 10.3233/JIFS-189174

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2020

Authors: Gongxiang, Huang, | Huimin, Qu,

Article Type: Research Article

Abstract: The influence of COVID-19 causes a certain impact on data visualization and data fusion on the visual performance of illustration. Based on the development of illustration, this paper discusses the relationship between illustration, text information and media. This paper studies the feasibility of the combination of illustration and information visualization. In this paper, the interactive image segmentation and gridding methods are proposed. Then, the background theory and significance of flow field design are described, and the flow field generation method based on heat source diffusion is proposed. In this paper, the shadow of the topology of the convective field through …the interaction input of the flow field design is analyzed, and then compared with the related work. In the visualization of flow field, based on the weighted distance field formed by the diffusion of heat source, a visualization method of stratified flow field line is proposed. Finally, the visualization method of stratified flow field is explained and its effect is demonstrated. Experimental data show that the information visualization method proposed in this paper can improve the efficiency and accuracy of illustration information extraction. Show more

Keywords: Illustration, media, information visualization, weighted distance field, COVID-19

DOI: 10.3233/JIFS-189276

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Jing, Jing

Article Type: Research Article

Abstract: The novel corona virus pneumonia has brought pressure on economic development. Large and medium-sized companies will also play a key role in the recovery of growth after the outbreak. Therefore, it is particularly important to pay attention to the impact of the epidemic on large and medium-sized companies and on the investment and financing of companies. Firstly, the structure of the network model of data analysis is designed in this paper, including the design of the network level, the selection of the number of neurons in each level, the determination of the initial weight and other related parameters. According to …the design of network structure, the evaluation model of investment and financing of listed companies is established. Python is used to preprocess the data and train the sample data. By comparing the data processed by two training methods, the optimal network classification model is selected. The experimental results show that the proposed method can improve the effectiveness of investment and financing decisions of listed companies. Show more

Keywords: COVID-19 epidemic situation, big data, investment decision, Relu function

DOI: 10.3233/JIFS-189285

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Gunjal, Sheetal D. | Raut, Rajeshree D. | Wagh, Abhay

Article Type: Research Article

Abstract: The paper presents integration of Discrete Wavelet Cosine Transform technique and Bacterial Foraging Algorithm (BFO) for the development and optimization of speech coder. It is depicted how by filtering the limited number of high energy components of transformed coefficients with parallel programming can maintain the speech signal quality in coding over wide range of bit rates. The performance of existing and proposed speech coding techniqueattributes such as compression ratio, coding delay, computational complexity and quality of reconstructed speech is examined for multiple bit rates and compared with other existing speech coding techniques in Matlab environment. The result showsimprovement in performancewith …respect to all attributes at the cost of increase in complexity. Show more

Keywords: Speech coder attributes, discrete wavelet cosine transform, bacterial foraging optimization, software defined radio

DOI: 10.3233/JIFS-189254

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Quadir, Abdul | Christy Jackson, J. | Prassanna, J. | Sathyarajasekaran, K. | Kumar, K. | Sabireen, H. | Ubarhande, Shivam | Vijaya Kumar, V.

Article Type: Research Article

Abstract: Domain name system (DNS) plays a critical part in the functioning of the Internet. But since DNS queries are sent using UDP, it is vulnerable to Distributed Denial of Service (DDoS) attacks. The attacker can take advantage of this and spoof the source IP address and direct the response towards the victim network. And since the network does not keep track of the number of requests going out and responses coming in, the attacker can flood the network with these unwanted DNS responses. Along with DNS, other protocols are also exploited to perform DDoS. Usage of Network Time Protocol (NTP) …is to synchronize clocks on systems. Its monlist command replies with 600 entries of previous traffic records. This response is enormous compared to the request. This functionality is used by the attacker in DDoS. Since these attacks can cause colossal congestion, it is crucial to prevent or mitigate these types of attacks. It is obligatory to discover a way to drop the spoofed packets while entering the network to mitigate this type of attack. Intelligent cybersecurity systems are designed for the detection of these attacks. An Intelligent system has AI and ML algorithms to achieve its function. This paper discusses such intelligent method to detect the attack server from legitimate traffic. This method uses an algorithm that gets activated by excess traffic in the network. The excess traffic is determined by the speed or rate of the requests and responses and their ratio. The algorithm extracts the IP addresses of servers and detects which server is sending more packets than requested or which are not requested. This server can be later blocked using a firewall or Access Control List (ACL). Show more

Keywords: Amplification attacks, DRDoS, domain name system, network time protocol

DOI: 10.3233/JIFS-189173

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Bo, Yang | Chunli, Wang

Article Type: Research Article

Abstract: Under the influence of the COVID-19, the analysis of physical health data is helpful to grasp the physical condition in time and promote the level of prevention and control of the epidemic. Especially for novel corona virus asymptomatic infections, the initial analysis of physical health data can help to detect the possibility of virus infection to some extent. The digital information system of traditional hospitals and other medical institutions is not perfect. For a large number of health data generated by smart medical technology, there is a lack of an effective storage, management, query and analysis platform. Especially, it lacks …the ability of mining valuable information from big data. Aiming at the above problems, the idea of combining Struts 2 and Hadoop in the system architecture of the platform is proposed in this paper. Data mining association algorithm is adopted and improved based on MapReduce. A service platform for college students’ physical health is designed to solve the storage, processing and mining of health big data. The experiment result shows that the system can effectively complete the processing and analysis of the big data of College students’ physical health, which has a certain reference value for college students’ physical health monitoring during the COVID-19 epidemic. Show more

Keywords: Physical health data, parallel processing, health monitoring, multi calculation big data, COVID-19

DOI: 10.3233/JIFS-189274

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Chen, Guo,

Article Type: Research Article

Abstract: In rural construction, affected by covid-19, it leads to the collection and demand survey of basic information data of relevant interest groups. The specific situation of the transformation of ancient villages is also gradually increasing. However, due to the complexity of rural space, the dispersion of settlement space and the diversity of information demand of rural planning work, the data coverage is large, information acquisition is difficult, the use effect of data collection is not ideal, and there is no planning feedback mechanism. However, during the epidemic period, the staff could not carry out a series of reconstruction of ancient …villages. At present, the data of village planning and construction and architectural design are complex, the needs of relevant interest groups are diversified, and regional planning is difficult. In this paper, the big data function is applied to the reconstruction of ancient villages in the epidemic period of covid-19. Show more

Keywords: Reconstruction of ancient villages, big data, regional co-ordination, rural architecture design, COVID-19

DOI: 10.3233/JIFS-189278

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Qian, Zhang

Article Type: Research Article

Abstract: The transmission routes of novel coronavirus pneumonia include direct transmission, aerosol transmission and contact transmission. Therefore, the novel coronavirus pneumonia has been spread very quickly. This has a certain impact on the development of graphic design. Graphic design plays an important role in product design. However, the traditional aided design method is too complex, and it is difficult for designers to design works that meet their own needs. In the design of 3D virtual vision graphics, the distance calculation of time series is not accurate. This kind of error will bring some errors to the design of complex curved surface …products. In order to measure the similarity of time series effectively, the calculation principle of Euclidean distance and dynamic bending distance is analyzed. Combined with the advantages of these two methods, a new distance calculation method based on morphological fitting is proposed. In this paper, through the research of ordered point sequence, the 3D virtual design method is used to improve the design effect, which has reference value for the design of works that meet the requirements of designers during the popularity of COVID-19. Show more

Keywords: 3D virtual graphic design, time series, distance calculation, shape fitting, COVID-19

DOI: 10.3233/JIFS-189269

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Caiqian, Zhang | Xincheng, Zhang

Article Type: Research Article

Abstract: The existing stand-alone multimedia machines and online multimedia machines in the market have certain deficiencies, so they cannot meet the actual needs. Based on this, this research combines the actual needs to design and implement a multi-media system based on the Internet of Things and cloud service platform. Moreover, through in-depth research on the MQTT protocol, this study proposes a message encryption verification scheme for the MQTT protocol, which can solve the problem of low message security in the Internet of Things communication to a certain extent. In addition, through research on the fusion technology of the Internet of Things …and artificial intelligence, this research designs scheme to provide a LightGBM intelligent prediction module interface, MQTT message middleware, device management system, intelligent prediction and push interface for the cloud platform. Finally, this research completes the design and implementation of the cloud platform and tests the function and performance of the built multimedia system database. The research results show that the multimedia database constructed in this paper has good performance. Show more

Keywords: Internet of things, cloud service platform, multimedia system, database

DOI: 10.3233/JIFS-189253

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Yong, Chang | Lu, Yun

Article Type: Research Article

Abstract: Under the influence of COVID-19, the efficiency of e-commerce distribution in public health emergencies has become the key to ensuring people’s normal lives. With the development of e-commerce, the location of distribution center is becoming more and more important, which is related to the healthy and long-term development of e-commerce. However, the traditional location efficiency is low, which cannot play an immediate role in the development of e-commerce. This paper combines weiszfeld algorithm, improves particle swarm optimization algorithm, improves the operation efficiency and location accuracy, and finally gets a relatively satisfactory result. Results data analysis shows that the improvement and …integration of the algorithm is reasonable and effective. This method has important reference value for e-commerce location. Show more

Keywords: E-commerce, center location, particle swarm optimization, Weiszfeld algorithm, COVID-19

DOI: 10.3233/JIFS-189275

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Yongkang, Li,

Article Type: Research Article

Abstract: In post COVID-19 era, labor education plays an indispensable part in China’s digital economy, while the digital economy will redefine the labor education at the same time. From the Marxist theory, latest data and survey results, we portray the logic relationships, mutual impacts between digital economy and labor education. Our research indicates that free development of all human beings is the common value shared by the digital economy and labor education. Labor education can cultivate the abilities of competition and cooperation, form the proper digital economy values meanwhile, which is essential to hedge the negative impacts of digital economy on …labor and employment. Labor education comprehensively promotes the digital labor abilities of all laborers in the path with Chinese characteristics. The boom in digital economy and the refocusing on labor education will enable China to cope with the rising risks and challenges in a more diversified and flexible way among this highly uncertain world. Show more

Keywords: Digital economy, labor education, COVID-19, neural network

DOI: 10.3233/JIFS-189281

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2020

Authors: Guanggen, Li | Matthews, Andrew

Article Type: Research Article

Abstract: The popularity of covid-19 has led to the introduction of the policy of controlling the flow of personnel, which has a certain impact on the color recognition of the design objects of hand decorative elements. In the past, the research on convolution neural network design and color recognition is still in the traditional method, and the field of computer vision is not really combined with the traditional decorative fabric. This paper proposes a solution based on deep learning. Color learning and main color recognition can be processed as a whole. By introducing convolution neural network, the scheme can learn color …features directly from the image itself, and the process of artificial design features is omitted. While simplifying the process of model building and training, the potential information association can be obtained, so as to obtain better recognition effect. In addition, due to the deep depth of the network, this paper uses the initial optimization module to avoid the performance degradation and over fitting in the training process. This method has an important reference value for the color design of modern hand decoration, and can promote the development of hand decoration during the popularity of covid-19. Show more

Keywords: CNN architecture, inception module, AVG pool, softmax, COVID-19

DOI: 10.3233/JIFS-189270

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Yuan, Luo | Xiaofei, Zhao | Yiyu, Qiu

Article Type: Research Article

Abstract: At present, the evaluation of normal teaching order and teaching quality has been seriously interfered by the impact of COVID-19. In order to ensure the quality of art classroom teaching, this article uses BP neural network technology to build a model for art teaching quality evaluation during the epidemic. Based on the introduction of the BP neural network model and the problems of art teaching quality evaluation, the article focuses on the art teaching quality evaluation indicators and the BP neural network algorithm and process. In addition, the article also uses an empirical method to verify the effect of the …BP network model training method, and obtains the expected effect. Finally, it discusses the problem of information processing in art teaching evaluation. Show more

Keywords: Art teaching quality evaluation, BP neural network, COVID-19

DOI: 10.3233/JIFS-189267

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Agrawal, Deepika | Pandey, Sudhakar | Gupta, Punit | Kumar Goyal, Mayank

Article Type: Research Article

Abstract: Wireless Sensor Networks is a complex network with millions of small-scale sensor nodes, working together to detect certain physical phenomena. Sensor nodes are operated by battery therefore the major concern is energy efficiency. Clustering is an effective technique to decrease the energy depletion in the network. However, choosing the optimum Cluster Heads is an NP-Hard problem. This paper proposes an unequal clustering technique that selects probationary Cluster Heads through fuzzy logic and the optimization of this probationary Cluster Heads is done through Harmony Search Algorithm (HSA). The proposed algorithm exhibits the dynamic capability of fuzzy logic and high search efficiency …of HSA that extends the network lifespan. The findings are simulated against traditional clustering protocols and compared. The findings obtained show that the protocol proposed is performing superior in terms of network lifespan prolongation and other metrics. Show more

Keywords: Optimal cluster heads, optimization, harmony search algorithm, wireless sensor networks, unequal clustering

DOI: 10.3233/JIFS-189175

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Tingting, Liang | Zhaoguo, Liu | Wenzhan, Wang

Article Type: Research Article

Abstract: The Covid-19 first occurs in Wuhan, China in December 2019. After that, the virus has spread all over the world and at the time of writing this paper the total number of confirmed cases are above 11 million with over 600,000 deaths. The pattern recognition of complex environment can be used to determine if a COVID-19 breath pattern can be established with accuracy. The traditional decorative pattern detection method has a high degree of recognition in simple scene. However, the efficiency of decorative pattern detection in complex scenes is low and the recognition accuracy is not high. Firstly, the evaluation …index of target detection method is designed. Through this paper, it is found that the success rate of some targets is naturally better than other targets, and easy to distinguish from the background. In order to improve the recognition success rate of the object in the complex environment and determine the position and attitude of the object, the pattern as the artificial identification in the environment is proposed. The interior art decoration pattern is selected as the experimental pattern and the pattern classification evaluation index is designed. The experimental results show that the method proposed in this paper can optimize the pattern subsets which are confused with each other and easy to distinguish from the background. It has a certain reference value for decorative pattern recognition in complex environment for COVID-19 epidemic. Show more

Keywords: Neural network, pattern classification, decorative pattern detection, complex environment, COVID-19

DOI: 10.3233/JIFS-189262

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Senthil, S. | Ravi, K.

Article Type: Research Article

Abstract: This paper illustrates a new compilation of Micro-grid by distributed energy sources using three phase three -level Space vector multilevel inverter. In olden days only 3Φ inverter was designed and they were connected to the consumer with higher harmonics without automatic control feeding power to the consumer end. But this system we implemented three phase three level inverter was fed power to the consumer and also reduces the switching losses. I have connected three renewable sources are alike Wind-turbine, P.V - cell and Pico-Hydel generator model to increases the potential of power supply to a relatively small jumble of …people, an official of the economic lay of a locality. Furthermore costless new semiconductor technologies in the power switches beside the necessity of current on giant consummation inverters necessitate by Renewable-Energy-Systems (R.E.S) by reduced Total-Harmonic-distortion (T.H.D) in the spectrum of switching waveform have expanded the applications of Multi-level inverters. This system also includes M.P.P.T electronic control to operate maximum point of modules so, it is supplying maximal power to the consumer connected load according to the changes in solar-radiation and diffusive-temperature and intern increase the battery charging current. Show more

Keywords: Renewable-energy-sources, micro-grid, multilevel- inverter, space-vector-modulation, reactive power –compensation and M.P.P.T algorithm

DOI: 10.3233/JIFS-189256

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2020

Authors: Guochen, Wan | Feihong, Shan

Article Type: Research Article

Abstract: During covid-19, basketball training was stopped. Instead, the basketball video analysis is used. In this paper, literature, theoretical analysis, numerical simulation, experimental research and other research methods are used. The ant colony algorithm model of deep learning optimization for basketball technical and tactical decision-making is established to solve the optimization problem of actual technical and tactical decision-making. In this paper, video image correlation algorithm is used. In the video of players’ free throw basket, there are many independent frames. The real frame set of free throw basket includes the whole process of jumping, arm lifting, squatting and stretching. The shooting …frame set and shooting information of the ball are obtained. In this paper, a shot frame detection algorithm is proposed by analyzing multiple samples of multi shot video. The mathematical model of the shooting frame is established, which can locate the shooting frame quickly and accurately and determine the penalty frame set. Further obtain the basketball release status information for preparation. The reliability and robustness of the algorithm are verified by experiments on several samples. It provides a new method for basketball training during covid-19. Show more

Keywords: Deep learning theory, video analysis, basketball training assistant, ant colony algorithm model

DOI: 10.3233/JIFS-189271

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Araújo Júnior, José M. | Linhares, Leandro L.S. | Araújo, Fábio M.U. | Almeida, Otacílio M.

Article Type: Research Article

Abstract: Newborns with health complications have great difficulty in regulating the body temperature due to distinct factors, which include the high metabolism rate and low weight. In this context, neonatal incubators help maintaining good health conditions because they provide a thermally-neutral environment, which is adequate to ensure the least energy expenditure by the newborn. In the last decades, artificial neural networks (ANNs) have been established as one of the main tools for the identification of nonlinear systems. Among the various approaches used in the identification process, the fuzzy wavelet neural network (FWNN) can be regarded as a prominent technique, consisting of …the combination of wavelet neural network (WNN) and adaptive network-based fuzzy inference system (ANFIS). This work proposes the use of FWNN to infer the temperature and humidity values inside the incubator in order to certify the equipment operation. Results obtained with the analyzed neural system have shown the generalization and inference capacities of FWNNs, thus allowing their application to practical tasks aiming to increase the efficiency of incubators. Show more

Keywords: Fuzzy wavelet neural networks, inferential sensors, neonatal incubators, system identification

DOI: 10.3233/JIFS-190129

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Yile, Wang, | Dashuai, Zeng,

Article Type: Research Article

Abstract: Based on big data, this paper studies the influence of new type of filling pneumonia on the development of sports industry. When selecting the typical economic indicators that reflect the development trend of sports industry, it is found that the data is huge according to the big industrial data, but the information that can be reflected is poor and complex. Therefore, it is necessary to process these big economic data in order to obtain the impact of new coronary pneumonia on the development of sports industry. This paper studies the feature selection algorithm of big data samples, so as to …select typical economic indicators from many economic indicators of sports industry to reflect the development trend of sports industry. A deep learning algorithm based on feature selection of big data is proposed. Firstly, a feature selection framework for big data is constructed, and then data fusion and deep learning are carried out. Experiments show that the algorithm can solve the contradiction between large data and poor information. This method has a certain forward-looking, and has a certain reference value for the information discrimination of the development trend of sports industry. Show more

Keywords: Sports industry, big data, industrial development, deep learning algorithm

DOI: 10.3233/JIFS-189284

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Lin, Tang

Article Type: Research Article

Abstract: Although much less fatal than the Ebola and previous SARS virus epidemics, the current coronavirus outbreak (COVID-19) has spread to more people in more countries in a much shorter time frame. With the rapid development of the Internet of things, it has played an important role to track/monitor transmission movements throughout the population. The technology infrastructure between mobile devices, wearable devices and sensors, smart home device makes it possible to readily deploy solutions to monitor and collect data and perform analysis to ensure policy make intelligent, rapid decisions. This research combines AOL and Support Vector Machine to form the Internet …of things cycle through smart home. The parameters of Support Vector Machine model are optimized by ALO algorithm, which shortens the learning time and improves the performance of classifier. Then, the algorithm of ALO is used to optimize the Support Vector Machine intrusion detection method and agent technology, and the intrusion detection model is established. Experimental results show that the combination of these two can effectively reduce the false alarm rate of network intrusion. Show more

Keywords: Support vector machine, intrusion detection, internet of things security, smart home

DOI: 10.3233/JIFS-189258

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Qiuling, Zheng | Ke, Yang | Qiang, Xu | Chenglong, Zhang | Liguang, Wang

Article Type: Research Article

Abstract: Under the influence of novel corona virus pneumonia, the staff are controlled. Therefore, it is a difficult problem to measure the parameters of wood structure building on site. The measurement error of traditional wood structure parameters in complex environment is large, so an efficient and accurate measurement and recognition method is needed. In this paper, a method combining random decrement method and ITD method is proposed to measure the frequency, damping ratio and other structural dynamic parameters of ancient building timber structure under crowd random load excitation. In this paper, the frequency and damping ratio of the typical ancient building …timber structure are predicted by using the artificial neural network model trained by the known data. The experimental results show that the population density has a great influence on the measurement of the dynamic parameters of the wooden structure of ancient buildings. Using this method, combined with the long-term monitoring data of temperature and humidity, the influence of various environmental factors on the dynamic characteristics of the structure can be analyzed. This provides data support for structural damage identification and health monitoring. Show more

Keywords: Artificial neural network (ANN), ITD method, population distribution density, dynamic characteristics, COVID-19

DOI: 10.3233/JIFS-189268

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2020

Authors: Zhihui, He, | Xiaofeng, Li,

Article Type: Research Article

Abstract: During the COVID-19 epidemic period, it is essential to strengthen physical exercise and improve the health of the whole people. In this paper, based on genetic algorithm, a fuzzy control system is proposed to dynamically adjust the exercise ability of the bodybuilders under the comprehensive consideration of parameters. Through experiments and data processing, the system obtains bioelectric information related to heart rate, heart rate variability and muscle fatigue of the fitness people in the three states of not fatigue, moderate fatigue and extreme fatigue, establishes fuzzy membership function, and thus establishes personalized fitness information feedback control strategy to maintain moderate …fitness intensity. By narrowing the gap between the predicted RPE value based on objective information and the measured RPE, the method provides a unified subjective and objective exercise intensity for the bodybuilders, effectively expands the time of aerobic exercise, and enhances the effect of aerobic exercise. In addition, in order to expand the scope of application of the exercise intensity control model, the service-oriented transformation is carried out to enable it to provide fitness content combinations of interest to fitness practitioners and instructors. Show more

Keywords: Fitness service technology, genetic algorithm, COVID-19

DOI: 10.3233/JIFS-189277

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Nagarajan, Manikandan | Sasikumar, A. | Muralidharan, D. | Rajappa, Muthaiah

Article Type: Research Article

Abstract: Approximate computing is a rapidly growing technique to speed up applications with less computational effort while maintaining the accuracy of error-resilient applications such as machine learning and deep learning. Inheritance properties of the machine and deep learning process give freedom for the designer to simplify the circuitry to speed up the computation process at the expense of accuracy of computational results. Fundamental blocks of any computation are adders. In order to optimize it for better performance, 2-bit multi-bit approximate adders (MAPX) are proposed in this work which breaks the lengthy carry chain. In contrast with other approximate larger width adders, …instead of using accurate adders for the most significant part, here proposed 2-bit MAPX-1 and MAPX-2 adders are arranged in various ways to compose most and least significant parts. Designed 8-bit and 16-bit adders are evaluated for their performance and error characteristics. Proposed 2-bit MAPX-2 shows better error characteristics whose MED is 0.250 while occupying less area and MAPX-1 consumes less power and delay at the cost of accuracy. Among the extended adders, MAPX 8-bit adder design1 outperforms the best performing APX based 8-bit adder design1. The error performance of it is improved by 14%, 42.1% and 50.4% compared to the existing well-performing APX 8-bit Design1, Design2 and Design3 respectively. Similarly, proposed MAPX 16-bit Design1 exhibits overwhelming performance compared to best performing APX 16-bit Design1, and its error performance is improved by 24.3%, 34.9% and 50.3% compared to APX 16-bit Design1, Design2 and Design3 respectively. In order to evaluate the proposed adder for a real application, extended MAPX 16-bit Design1 is fit in the convolution layer of Low Weights Digit Detector (LWDD) convolutional neural network-based digit classification system. Our modified system accelerates the computation process by 1.25 factors while exhibiting the accuracy of 91% and it best fits error-tolerant real applications. All the adders are synthesized and implemented in the Intel Cyclone IV EP4CE22F17C6N FPGA. Show more

Keywords: Approximate adders, multi-bit adders, CNN accelerator, digit classification, deep learning

DOI: 10.3233/JIFS-189169

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Martinaa, M. | Santhi, B. | Raghunathan, A.

Article Type: Research Article

Abstract: Wireless Sensor Networks (WSNs) is created, stemming from their applications in distinct areas. Huge sensor nodes are deployed in geographically isolated regions in WSN. As a result of uninterrupted transmission, the energy level of the nodes gets rapidly depleted. Sensor node batteries cannot be replaced or recharged often and maintaining the energy level is a crucial issue. Thus energy efficiency is the significant factor to be consider in WSN. This paper focuses to implement an efficient clustering and routing protocols for maximized network lifetime. Clustering has been confirmed as a successful approach in network organization. The fundamental responsibilities of the …clustering mechanism include improved energy efficiency and extended network lifespan. In this work, energy efficiency is improved to maximize lifespan of the WSN by proposing a novel method known as the Populated Cluster aware Routing Protocol (PCRP). The proposed method comprises three different steps: cluster formation, cluster head selection, and multi-hop data transmission. All sensor nodes are joined to a Cluster Head in a single hop in the cluster formation phase. Node distance is calculated and from which cluster head is selected. Then, cluster head aggregates the data from sensor nodes and transfer to the Base Station (BS). The shortest pathway is estimated by the Energy Route Request Adhoc On-demand Distance Vector (ERRAODV) algorithm. The proposed method considers the residual energy involved to attain high energy efficiency and network stability. The experimental analysis is demonstrated to validate the proposed method with existing, which improves the network lifespan. Vital parameters are validated using Network Simulator (NS2). Show more

Keywords: Energy consumption, clustering, routing protocol, network lifetime, wireless sensor networks

DOI: 10.3233/JIFS-189170

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2020

Authors: Varghese, Lijo Jacob | Sira Jacob, Suma | Banumathi, S. | Ravi, Logesh | Vairavasundaram, Subramaniyaswamy | Jacob Raglend, I.

Article Type: Research Article

Abstract: This work aims to improve the operation of multi-level inverter with reduced switching losses, thereby propose a new structure for an MLI with a reduced component count. A 27-level asymmetric Multi Level Inverter (MLI) with a minimal number of static switches is considered as a test system. The proposed MLI is developed with three input DC sources and thirteen power electronic switches. The hardware prototype is developed for 40 V and 3.5 A output. The control logic is developed in dsPIC30F410 controller. The main objective of this work is to effectively bring down the Total Harmonic Distortion (THD) of the resulting …output voltage by analyzing the harmonic spectrum of the proposed MLI configuration with various low frequencies switching techniques and optimizing their switching angles and to choose an appropriate switching state using fuzzy logic controller (FLC). The proposed FLC covers wide range of operating conditions i.e. 10 switching states and variables 9*9 rules to predict the suitable switching angel. The performance metrics of the proposed structure of 27-level MLI has been evaluated upon simulation results and experimental results based on hardware prototype. The comparative study also carried out with the recent MLI topologies. Show more

Keywords: Asymmetric multilevel inverter, fuzzy logic, total harmonic distortion, pulse width modulation, reduced number of switches, optimum switching angles.

DOI: 10.3233/JIFS-189168

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Jagdish, Mukta | Viloria, Amelec | Vargas, Jesus | Pineda Lezama, Omar Bonerge | Ovallos-Gazabon, David

Article Type: Research Article

Abstract: Cloud-based computation is known as the source architecture of the upcoming generation of IT enterprise. In context to up-coming trade solutions, the Information Technology sections are established under logical, personnel, and physical control, it transfers application software and large database to appropriate data centers, where security and management of database with services are not trustworthy fully. So this process may face many challenges towards society and organizations and that not been well understood over a while duration. This becomes one of the major challenges days today. So in this research, it focuses on security-based data storage using cloud, which plays …one of the important aspects bases on qualities of services. To assure user data correctness in the cloud system, a flexible and effective distributed technique with two different salient features was examined by utilizing the token called homomorphic with erasure-coded data for distributed verification, based on this technique it achieved error data localization and integration of storage correctness. Also, it identifies server misbehaving, efficient, and security-based dynamic operations on data blocking such as data append, delete, and update methods. Performance analysis and security show the proposed method is more effective resilient and efficient against Byzantine failure, even server colluding attacks and malicious data modification attacks. Show more

Keywords: Cloud security, architecture design, data storage, homomorphic token, dynamic operation

DOI: 10.3233/JIFS-189172

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Sekar, K. R. | Thaventhiran, C. | Sathiamoorthy, G.

Article Type: Research Article

Abstract: Vitiligo is a problem due to the destruction of melanocytes which is present in 1% of people all over the world. The origin of this disease is unknown and difficult to cure. Absence of melanin in the body causes lesions which will ooze out all over the body. Phototherapy and surgical therapy are the two types of treatment available in the existing world. The Cytotoxic CD8 + T lymphocytes act as a major factor for the abovesaid disease. The main objective of this work is to treat patients with different methods according to the severity of vitiligo, which can be identified with …the help of out ranking based on hesitant fuzzy relation. Multi-criteria and multi-objective hesitant fuzzy are applied in this work to find out the ranking through which the severity of the disease is detected. This method helps in identifying the vitiligo lesions, which can be treated effectively in a short period of time. During the application of vitiligo treatment, FQA-TOPSIS (Fuzzy Quantified Attribute-TOPSIS) hesitant fuzzy relation methodology is deployed with three decision maker’s support using linguistic and intuitionistic values. The decision maker’s fuzzy values will be normalized and aggregated in this work with improved methodologies. The two objectives are deployed with their own fuzzy values and are implemented in the decision maker’s values. In the article fuzzy weightage has been calculated in two ways. One is every linguistic like low, medium, high and very high has got its significant intuitionistic values that all will be available with the scale of 1 to 10. The same has given as triplets. In our research work the above said has applied with the objective based weightage. So the accuracy has been increased through the work. The outcome of this methodology is to find out the coefficient closeness of the alternatives and to out rank the decision alternatives. The difference between the Final +ve Ideal Solution (FPIS) and Final -ve Ideal Solution (FNIS) is determined and FQA-TOPSIS Hesitant Fuzzy is ranked in the result. Show more

Keywords: FQA-TOPSIS, hesitant fuzzy, cytotoxic, vitiligo, melanocytes, final positive ideal solution and final -ve ideal solution

DOI: 10.3233/JIFS-189162

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Yun, Yong Sik

Article Type: Research Article

Abstract: We generalized triangular fuzzy numbers from ℝ to ℝ 2 . By defining parametric operations between two α -cuts, which are regions, we obtained parametric operations for two triangular fuzzy numbers defined on ℝ 2 . We also generalized triangular fuzzy numbers from ℝ 2 to ℝ 3 . By defining parametric operations between two α -cuts, which are subsets of ℝ 3 …, we derived parametric operations for two triangular fuzzy numbers defined on ℝ 3 . For the calculation of Zadeh’s principle operators, the definition of parametric operations between two α -cuts, which are subsets of ℝ 3 , is critical. Show more

Keywords: Zadeh’s max-min composition operator, 3-dimensional triangular fuzzy number, 47N99

DOI: 10.3233/JIFS-192095

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Song, Zekun | Li, Haodong | Shi, Jintang

Article Type: Research Article

Abstract: Service accessibility can be used to describe the travel time of passengers between different nodes, and opportunities to get transportation services in the high-speed railway (HSR) system. Based on the traditional train line planning theory, this paper introduces the transportation service accessibility index, and propose a new nonlinear passenger train line planning model, which aims to maximize the service accessibility, as well as minimize the operational cost of railway company. The model is transformed into a single-objective model, and then we design a harmony search algorithm to solve it. Finally, the model is validated by a numerical example. The results …of this model as well as the scenarios of the single-objective models for minimizing operational costs and maximizing service accessibility are compared. From the perspective of service frequency and accessibility of each nodes, we know that the proposed method can balance conflicts between average speed between large nodes and service frequency of small and medium size nodes in high-speed railway network. Show more

Keywords: High-speed railway, train line plan, service accessibility, harmony search algorithm, multi-objective optimization

DOI: 10.3233/JIFS-191866

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Basiri, Mohammad-Ali | Alinezhad, Esmaeil | Tavakkoli-Moghaddam, Reza | Shahsavari-Poure, Nasser

Article Type: Research Article

Abstract: This paper presents a multi-objective mathematical model for a flexible job shop scheduling problem (FJSSP) with fuzzy processing times, which is solved by a hybrid intelligent algorithm (HIA). This problem contains a combination of a classical job shop problem with parallel machines (JSPM) to provide flexibility in the production route. Despite the previous studies, the number of parallel machines is not pre-specified in this paper. This constraint with other ones (e.g., sequence-dependent setup times, reentrant workflows, and fuzzy variables) makes the given problem more complex. To solve such a multi-objective JSPM, Pareto-based optimization algorithms based on multi-objective meta-heuristics and multi-criteria …decision making (MCDM) methods are utilized. Then, different comparison metrics (e.g., quality, mean ideal distance, and rate of achievement simultaneously) are used. Also, this paper includes two major phases to provide a new model of the FJSSP and introduce a new proposed HIA for solving the presented model, respectively. This algorithm is a hybrid genetic algorithm with the SAW/TOPSIS method, namely HGASAW/HGATOPSIS. The comparative results indicate that HGASAW and HGATOPSIS outperform the non-dominated sorting genetic algorithm (NSGA-II) to tackle the fuzzy multi-objective JSPM. Show more

Keywords: Flexible job shop scheduling, multi-objective optimization, sequence-dependent setup times, multi-criteria decision making, hybrid intelligent algorithms.

DOI: 10.3233/JIFS-201120

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2020

Authors: Wei, Lixin | Zhang, JinLu | Fan, Rui | Li, Xin | Sun, Hao

Article Type: Research Article

Abstract: In this article, an effective method, called an adaptive covariance strategy based on reference points (RPCMA-ES) is proposed for multi-objective optimization. In the proposed algorithm, search space is divided into independent sub-regions by calculating the angle between the objective vector and the reference vector. The reference vectors can be used not only to decompose the original multi-objective optimization problem into a number of single-objective subproblems, but also to elucidate user preferences to target a preferred subset of the whole Pareto front (PF). In this respect, any single objective optimizers can be easily used in this algorithm framework. Inspired by the …multi-objective estimation of distribution algorithms, covariance matrix adaptation evolution strategy (CMA-ES) is involved in RPCMA-ES. A state-of-the-art optimizer for single-objective continuous functions is the CMA-ES, which has proven to be able to strike a good balance between the exploration and the exploitation of search space. Furthermore, in order to avoid falling into local optimality and make the new mean closer to the optimal solution, chaos operator is added based on CMA-ES. By comparing it with four state-of-the-art multi-objective optimization algorithms, the simulation results show that the proposed algorithm is competitive and effective in terms of convergence and distribution. Show more

Keywords: Multi-objective optimization problem, Reference point, Covariance matrix adaptation evolutionary strategy, Chaos operator

DOI: 10.3233/JIFS-200749

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2020

Authors: Xiaohua, Liu,

Article Type: Research Article

Abstract: In the face of the current epidemic situation, news reports are facing the problem of higher accuracy. The speed and accuracy of public emergency news depends on the accuracy of web page links and tags clustering. An improved web page clustering method based on the combination of topic clustering and structure clustering is proposed in this paper. The algorithm takes the result of web page structure clustering as the weight factor. Combined with the web content clustering by K-means algorithm, the basic content that meets the conditions is selected. Through the improved translator of clustering algorithm, it is translated into …Chinese and compared with the target content to analyze the similarity. It realized the translation aim of new crown virus epidemic related news report of Japanese Linguistics based on page link mining. Show more

Keywords: Web community, link structure, page link mining, minimum description length

DOI: 10.3233/JIFS-189296

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Bing, Zheng, | Dawei, Yun, | Yana, Liang,

Article Type: Research Article

Abstract: Under the impact of COVID-19, research on behavior recognition are highly needed. In this paper, we combine the algorithm of self-adaptive coder and recurrent neural network to realize the research of behavior pattern recognition. At present, most of the research of human behavior recognition is focused on the video data, which is based on the video number. At the same time, due to the complexity of video image data, it is easy to violate personal privacy. With the rapid development of Internet of things technology, it has attracted the attention of a large number of experts and scholars. Researchers have …tried to use many machine learning methods, such as random forest, support vector machine and other shallow learning methods, which perform well in the laboratory environment, but there is still a long way to go from practical application. In this paper, a recursive neural network algorithm based on long and short term memory (LSTM) is proposed to realize the recognition of behavior patterns, so as to improve the accuracy of human activity behavior recognition. Show more

Keywords: Recurrent neural network, behavior recognition, time series analysis, automatic coder

DOI: 10.3233/JIFS-189290

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Wu, Xiu-Yun

Article Type: Research Article

Abstract: On completely distributive lattice, the notion of fuzzy generalized convex space is introduced. It can be characterized by many means including fuzzy generalized hull space, fuzzy generalized restricted hull space, fuzzy generalized convexly enclosed relation space and fuzzy generalized derived hull space.

Keywords: Fuzzy generalized convex space, fuzzy generalized hull space, fuzzy generalized restricted hull space, fuzzy generalized convexly enclosed relation space

DOI: 10.3233/JIFS-200026

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Parsa, Navid | Bahmani-Firouzi, Bahman | Niknam, Taher

Article Type: Research Article

Abstract: Distribution automation is well recognized as an effective solution to enhance the reliability and efficiency of these grids in a timely manner. This paper introduces an effective probabilistic operation framework for the automated distribution networks (ADNs) incorporating the plug-in electric vehicles (PEVs) charging/discharging schemes in the presence of different renewable energy sources (RESs). To this end, this paper pursues four different strategic approaches. Firstly, an effective fuzzy based probabilistic method is proposed to model the forecast error in the wind and solar units well as the load demand through the cloud theory. Secondly, an appropriate framework is devised to model …the PEVs random behaviour considering their essential parameters such as the charging/discharging rate and arrival/departure time to/from the parking lots (PLs), the discharging level at driving mode on the road and the effects of battery degradation. As the third goal, an appropriate objective function which can consider automation indices including the social welfare and reliability is considered. Since the operation problem is a nonlinear continuous non-numerical problem, it requires an applicable and effective optimization algorithm which is regarded as the fourth goal of this paper. In this regard, a new θ -modified bat algorithm is introduced to find the optimal solution of the problem. The proposed model is simulated and examined on the IEEE 69-bus standard test system wherein results reveal the effectiveness and applicability of the proposed operation management framework. Show more

Keywords: Automated distribution networks, reliability, electric vehicles, renewable energy sources, optimization and operation management

DOI: 10.3233/JIFS-200246

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2020

Authors: Jihong, Yang | Lu, Yun

Article Type: Research Article

Abstract: Under the influence of novel corona virus pneumonia epidemic prevention and control, higher requirements for behavior recognition in complex environment are put forward. The accuracy of traditional methods for sports training is not high, so a method is needed to improve the local action recognition to assist sports training. In the process of behavior recognition, if only the track is regarded as an independent individual, the information of its neighbor will be ignored. Therefore, we use KNN algorithm to get the nearest neighbor trajectory. In order to calculate the rich neighborhood information around the track, this paper calculates the complex …relationship between the center track and the neighborhood track from four different angles, including absolute motion, relative motion, distance relationship and direction relationship. Then, from the four different perspectives of variance, discrete coefficient, skewness and kurtosis, this paper proposes a large interval nearest neighbor coding method. This method makes the four eigenvalues complement each other and improves the ability of describing complex and changeable behaviors. The experimental results show that the coding method proposed in this paper can be used for behavior recognition according to different transformation matrix. Show more

Keywords: Behavior recognition, track space-time feature, feature matching, fuzzy set

DOI: 10.3233/JIFS-189263

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Varela, Noel | Pineda Lezama, Omar Bonerge | Neira, Harold

Article Type: Research Article

Abstract: The principle assaults on a Wireless Sensor Network (WSN) essentially influence the uprightness and accessibility of the data gathered, for example, Deni-al of Service, Blackhole, Wormhole, and assault on the data being transmitted. Privacy is not an important security objective because the data caught by the sensors are typically not delicate or mystery from individuals. A remote sensor organizes applied to shrewd metering frameworks might be adequately powerful as far as robotization and adjustment of the information that is gathered, however, if the system doesn’t have satisfactory security, both the client and the organization offering the support might be influenced …by assaults on the respectability and accessibility of the data transmitted. This research proposes the use of MESH encryption techniques and Star topology to find the best combination that meets the requirements of a Smart Metering System. Show more

Keywords: Security, encryption, topology, WSN, smart metering networks, cryptographic techniques

DOI: 10.3233/JIFS-189167

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Gang, Li | Fang, Wang | Sishi, Quan

Article Type: Research Article

Abstract: COVID-19’s significant impact on economic and social life has rightfully garnered the attention of citizens and policymakers alike. In response to the pandemic, governments have issued strict guidelines and restrictions to shut down some cities and many rural villages in China. With no cure or vaccine on the horizon, governments are working to mitigate the damage of the lockdowns on rural cultural village. Over the past two decades, rural village has been negatively impacted by terrorism, lack of funding and loss of population. COVID-19 has had similar effect, but in an incredibly short period of time. During the control period …of COVID-19, traditional data are widely used in village protection and renewal. Collect and sort out the original data of Huizhou culture to prepare for the subsequent calculation. After the data is ready, the data is processed as the basis of mining its potential application value. In this paper, the key words of Huizhou cultural resources are summarized. The data analysis platform is established. This paper analyzes people’s preference for Huizhou cultural resources. To better realize the more effective and far-reaching development and exploitation of Huizhou cultural resources. Show more

Keywords: Big data, Huizhou traditional village cultural resources, cultural heritage, mining applications, COVID-19

DOI: 10.3233/JIFS-189264

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Imran, Muhammad | Akhter, Shehnaz | Shaker, Hani

Article Type: Research Article

Abstract: Inequalities are a useful method to investigate and compare topological indices of graphs relatively. A large collection of graph associated numerical descriptors have been used to examine the whole structure of networks. In these analysis, degree related topological indices have a significant position in theoretical chemistry and nanotechnology. Thus, the computation of degree related indices is one of the successful topic of research. Given a molecular graph H , the general Randić connectivity index is interpreted as R α ( H ) = ∑ ℛ ∈ E ( H ) ( …deg H ( a ) deg H ( b ) ) α , with α is a real quantity. Also a graph transformation of H provides a comparatively simpler isomorphic structure with an ease to work on different chemical properties. In this article, we determine the sharp bounds of general Randić index of numerous graph transformations, such that semi-total-point, semi-total-line, total and eight individual transformations H fgh , where f , g , h  ∈ {+ , -} of graphs by using combinatorial inequalities. Show more

Keywords: General Randić index, transformation graph, semi-total-point graph, semi-total-line graph

DOI: 10.3233/JIFS-201139

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Murugaboopathi, G. | Gowthami, V.

Article Type: Research Article

Abstract: Privacy preservation in data publishing is the major topic of research in the field of data security. Data publication in privacy preservation provides methodologies for publishing useful information; simultaneously the privacy of the sensitive data has to be preserved. This work can handle any number of sensitive attributes. The major security breaches are membership, identity and attribute disclosure. In this paper, a novel approach based on slicing that adheres to the principle of k -anonymity and l -diversity is introduced. The proposed work withstands all the privacy threats by the incorporation of k-means and cuckoo-search algorithm. The experimental results with …respect to suppression ratio, execution time and information loss are satisfactory, when compared with the existing approaches. Show more

Keywords: Privacy preservation, slicing, k-anonymity, l-diversity

DOI: 10.3233/JIFS-189257

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Zhaoguo, Liu | Tingting, Liang | Wenzhan, Wang

Article Type: Research Article

Abstract: Under the influence of novel corona virus pneumonia epidemic, the protection of traditional villages is put forward higher request. The spread of the epidemic among villages will make the situation of epidemic prevention and control more difficult. As an important part of culture, traditional villages have high historical value. In this paper, the traditional village protection method, a new geographical data algorithm IData storage method. Compared with the traditional ArcGIS method, it improves the efficiency and accuracy of topographic map entry. IData’s data factory can use the symbolic technology of skeleton lines to represent all the figures in the national …standard mode, and any complex figure can only be represented by one element. Idate can quickly load data and render symbols in a drawing. With the powerful data processing engine of IData data factory, we can check out the errors that other software can’t find and process the data automatically. Records of the loss of traditional villages can be recorded quickly. The establishment and protection of traditional villages have had a beneficial impact. Show more

Keywords: Traditional village protection, big data, COVID-19, ArcGIS

DOI: 10.3233/JIFS-189261

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Weining, Sun | Cheli, Zhao

Article Type: Research Article

Abstract: During COVID-19 pandemic, researchers have used innovative technologies for fast tracking the development to end this pandemic. Virtual Reality (VR) has offered an imperative role for fighting this pandemic, through audiovisual-based virtual communication. Virtual reality modeling language (VRML), as an international standard of virtual reality, has developed rapidly. VRML expanded the function of script node by introducing Java and script programs written in java script language. This paper presents a VRML method. Libraries and platoons are virtualized to meet the normal use of users. In principle, any text editing system can be used for VRML programming, but some editing systems …have few related functions and are not suitable for large-scale VRML Scene Design. The VRML algorithm proposed in this paper can be applied to large buildings. The VRML algorithm proposed in this paper is compared with the traditional algorithm. The VRML algorithm proposed in this paper is superior to the traditional algorithm in the aspects of realism, interactivity, design rationality and execution speed. The practicability of the VRML algorithm is proved. It provides help for people who are inconvenient to go out during the protection period of covid-19. Show more

Keywords: Virtual reality modeling language virtual library, virtual volleyball hall, 3D, Internet, system

DOI: 10.3233/JIFS-189260

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Nourbakhsh, Azamossadat | Moin, Mohammad-Shahram | Sharifi, Arash

Article Type: Research Article

Abstract: Face is the most important and most popular biometric used in many identification and verification systems. In these systems, for reducing recognition error rate, the quality of input images need to be as high as possible. Face Image Compliancy verification (FICV) is one of the most essential methods for this purpose. In this research, a brain functionality inspired model is presented for FICV using Haxby model, which is a face visual perception consistent model containing three bilateral areas for three different functionalities. As a result, contribution of this work is presenting a new model, based on human brain functionality, improving …the compliancy verification of face images in FICV context. Perceptual understanding of an image is the motivation of most of the quality assessment methods, i.e., the human quality perception is considered as a gold standard and a perfect reference for recognition and quality assessment. The model presented in this work aims to make the operational process of face image quality assessment system closer to the performance of a human expert. Three basic modules have been introduced. Face structural information, for initial information encoding, is simulated by an extended Viola-Jones model. Face image quality assessment is presented by International Civil Aviation Organization (ICAO), in ICAO (ISO / IEC19794 -11) requirements’ compliancy assessment document. Like Haxby model, perception is performed through two distinct functional and neurological pathways, using Hierarchical Maximum pooling (HMAX) and Convolutional Deep Belief Networks (CDBN). Information storing and fetching for training are similar to their corresponding modules in brain. For simulating the brain decision making, the final results of two separate paths are integrated by weighting sum operator. Nine ISO / ICAO requirements were used for testing the model. The simulation results, using AR and PUT databases, shows improvements in six requirements using the proposed method, in comparison with the FICV benchmark. Show more

Keywords: Haxby model, ICAO, facial images quality verification, HMAX model, CDBN

DOI: 10.3233/JIFS-189171

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Renjini, G.S. | Deepa, T.

Article Type: Research Article

Abstract: DC-DC converters are widely used in many consumer electronic devices such as computers, medical equipment, battery chargers, cellular phones and many Industrial drives. These electronic devices require different voltage levels which is supplied from battery or some external supply. In multiple battery mission voltage decays as its stored energy is drained and requires large saving space. The switched DC-DC converters overcome these drawbacks and also regulate the output voltage for different power levels efficiently. This paper elaborates the structure of Luo converter with optimized PI controller. Positive Output Elementary Luo Converter (POELC) is designed for boost operation by choosing the …appropriate duty cycle. The PI controller parameters are optimized using Cuckoo and Crow search algorithms. The proposed control methods are investigated for the transient and steady state region. The sensitivity of these controllers to supply load and line disturbances are also studied along with the servo response are presented. The controller incorporates a Luo converter is evaluated in terms of Integral Time Square Error (ITSE) and Integral Time Absolute Error. Dynamic modelling of the power converter is derived by using state space averaging method. The simulation model of the Luo converter with its control circuit is implemented in MATLAB/SIMULINK. Experimental result shows that Cuckoo PI controller has significantly performance improvement in comparison with both the conventional and Crow PI controller. Show more

Keywords: Positive output elementary luo converter (POELC), cuckoo search optimization, crow search optimization, proportional – integral (PI), ziegler nichols (ZN), pade routh approximation

DOI: 10.3233/JIFS-189255

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Chen, Haixia

Article Type: Research Article

Abstract: Innovation and entrepreneurship are an important support for social and economic development in the new era, and it is also the key to the cultivation of practical talents in universities. In order to mine the effective information of innovation and entrepreneurship data, based on the neural network algorithm, this paper combines the bat algorithm to construct a data processing model to obtain an artificial intelligence innovation and entrepreneurship system with data analysis capabilities. Moreover, this study combines with actual needs to improve the algorithm, effectively eliminate the noise existing in the data, eliminate the interference of invalid data on the …judgment ability of the system model, and choose the best denoising algorithm through comparison and verification of various algorithms. In order to verify the model proposed in this paper, the data is input into this research model by collecting data in a college survey, so as to verify and analyze the performance of the model. The research results show that the artificial intelligence system proposed in this paper has good performance and has certain practical value. Show more

Keywords: Artificial intelligence, neural network, improved algorithm, innovation and entrepreneurship

DOI: 10.3233/JIFS-189245

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Zhenhua, Liu | Mengting, Zhang | Yupeng, Li | Xuening, Chu

Article Type: Research Article

Abstract: The evolution of the product family is the essential driving force for the development of a complex product. Only customer satisfaction is emphasized in the traditional module configuration methods, which is not beneficial for product family evolution that is due to non-customer factors such as the emergence of new technology. In this study, the intuitionistic fuzzy number is employed to quantify the degree of correlation between each module and configuration targets, namely customer satisfaction and the degree of evolution of the product family, respectively. The bi-objective integer programming model is constructed by maximizing the degree of customer satisfaction and product …family evolution. An improved Pareto ant colony optimization (P-ACO) is designed to solve this model and subsequently the Pareto frontier is obtained. The radar chart is adopted to represent the performance of each configuration scheme in the Pareto frontier. The feasibility and effectiveness of the proposed method are expounded by a case study and result comparison, showing that this method can provide a more competitive product configuration scheme to customers in the future market. Show more

Keywords: Product family evolution, complex products, module configuration, customer requirements, P-ACO

DOI: 10.3233/JIFS-200527

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-19, 2020

Authors: Dongmei, Li

Article Type: Research Article

Abstract: English text-to-speech conversion is the key content of modern computer technology research. Its difficulty is that there are large errors in the conversion process of text-to-speech feature recognition, and it is difficult to apply the English text-to-speech conversion algorithm to the system. In order to improve the efficiency of the English text-to-speech conversion, based on the machine learning algorithm, after the original voice waveform is labeled with the pitch, this article modifies the rhythm through PSOLA, and uses the C4.5 algorithm to train a decision tree for judging pronunciation of polyphones. In order to evaluate the performance of pronunciation discrimination …method based on part-of-speech rules and HMM-based prosody hierarchy prediction in speech synthesis systems, this study constructed a system model. In addition, the waveform stitching method and PSOLA are used to synthesize the sound. For words whose main stress cannot be discriminated by morphological structure, label learning can be done by machine learning methods. Finally, this study evaluates and analyzes the performance of the algorithm through control experiments. The results show that the algorithm proposed in this paper has good performance and has a certain practical effect. Show more

Keywords: Machine learning, English, text-to-speech conversion, improved algorithm, simulation

DOI: 10.3233/JIFS-189238

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Qianna, Sun

Article Type: Research Article

Abstract: The intelligent evaluation of classroom teaching quality is one of the development directions of modern education. At present, some teaching quality evaluation models have accuracy problems, and the evaluation process is affected by a variety of interference factors, which leads to inaccurate model results, and it is impossible to find out the specific factors that affect teaching. In order to improve the accuracy of classroom teaching quality evaluation, this study improves RVM based on the method of feature extraction and empirical modal decomposition of ACLLMD method, and establishes classroom theoretical teaching quality evaluation model and experimental teaching quality evaluation model …based on RVM algorithm. Moreover, this study uses test data to analyze the accuracy and reliability of the evaluation results to verify the feasibility and reliability of the new method. In addition, this study verifies the reliability of this algorithm by comparing with the manual scoring results. The research results show that RVM can be used to construct classroom theory teaching quality evaluation models and experimental teaching quality evaluation models with high accuracy and good reliability. Show more

Keywords: Improved algorithm, neural network, path sequencing, network teaching, knowledge recommendation

DOI: 10.3233/JIFS-189240

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Kaul, Sonam Devgan | Hatzinakos, Dimitrios

Article Type: Research Article

Abstract: In this work, we will be investigating, developing and implementing an intelligent RFID system in conjunction with a fuzzy data classification system, to greatly enhance and secure financial transactions and improve operational efficiency in the banking environment. The innovative part of this research is to provide an efficient solution to the challenge that may arise from the need to expertly and automatically match the profile of customer and banker and solve the vagueness in customer/banking profiling. Our proposal offers an expert, secure, efficient and comprehensive framework, methodology and its application in financial environments to develop customer to banker profile matching …and availability via an expert agent multi level fuzzy data classification system. Foremost, according to clients and banking staff members weighted attributes, exact match has been established according to highest degree of relevance by utilizing Matlab fuzzy inference system. Then, to communicate output of a match profile engine from one party to another, to show profiling effectiveness and to do implementation; secure, privacy preserving, and comprehensive intelligent RFID profiling authentication system has been designed and verified by Scyther tool. Show more

Keywords: Authentication system, fuzzy inference system, intelligent system, matlab, profiling system, RFID, Scyther

DOI: 10.3233/JIFS-191480

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-20, 2020

Authors: Qianyun, Yang | Xiaoyan, Wang

Article Type: Research Article

Abstract: The increasing complexity of the financial system has increased the uncertainty of the market, which has led to the complexity of the evolution of limited rational investor behavior decisions. Moreover, it also has a negative effect on the market and affects the development of the real economy and social stability. In view of the interconnected characteristics of various elements presented in financial complexity, based on complex network theory, Bayesian learning theory and social learning theory, this study systematically describes the behavioral decision-making mechanism of individual investors and institutional investors from the perspective of network learning. In addition, this study builds …an evolutionary model of investor behavior based on Bayesian learning strategies. According to the results of the horizontal and vertical bidirectional studies simulated by experiments, we can see that the method proposed in this study has a certain effect on the evaluation and decision support of stock market investment. Show more

Keywords: Bayesian learning, stock market, investment behavior, behavior simulation

DOI: 10.3233/JIFS-189242

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Habib, Shaista | us Salam, Wardat | Butt, M. Arif | Akram, M. | Smarandache, F.

Article Type: Research Article

Abstract: Cardiovascular diseases are the leading cause of death worldwide. Early diagnosis of heart disease can reduce this large number of deaths so that treatment can be carried out. Many decision-making systems have been developed, but they are too complex for medical professionals. To target these objectives, we develop an explainable neutrosophic clinical decision-making system for the timely diagnose of cardiovascular disease risk. We make our system transparent and easy to understand with the help of explainable artificial intelligence techniques so that medical professionals can easily adopt this system. Our system is taking thirty-five symptoms as input parameters, which are, gender, …age, genetic disposition, smoking, blood pressure, cholesterol, diabetes, body mass index, depression, unhealthy diet, metabolic disorder, physical inactivity, pre-eclampsia, rheumatoid arthritis, coffee consumption, pregnancy, rubella, drugs, tobacco, alcohol, heart defect, previous surgery/injury, thyroid, sleep apnea, atrial fibrillation, heart history, infection, homocysteine level, pericardial cysts, marfan syndrome, syphilis, inflammation, clots, cancer, and electrolyte imbalance and finds out the risk of coronary artery disease, cardiomyopathy, congenital heart disease, heart attack, heart arrhythmia, peripheral artery disease, aortic disease, pericardial disease, deep vein thrombosis, heart valve disease, and heart failure. There are five main modules of the system, which are neutrosophication, knowledge base, inference engine, de-neutrosophication, and explainability. To demonstrate the complete working of our system, we design an algorithm and calculates its time complexity. We also present a new de-neutrosophication formula, and give comparison of our the results with existing methods. Show more

Keywords: Single-valued neutrosophic number, explainable artificial intelligence, cardiovascular diseases, decision making, de-neutrosophication, algorithm

DOI: 10.3233/JIFS-201163

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-23, 2020

Authors: Qu, Xiaojuan

Article Type: Research Article

Abstract: Aiming at the actual problems encountered in the specific poverty alleviation work, this article designs a management system specifically designed for poverty alleviation workers to solve poverty alleviation data sharing and online editing and uploading of poverty alleviation logs. Based on the neural network and network characteristics, a system model is constructed, and the application of structural disturbance theory in dynamic networks is studied. Moreover, in this study, the dynamic change information between time-series networks is taken into account for structural disturbances. By combining structural disturbances and local topology, a new similarity measurement method suitable for dynamic networks is proposed. …In addition, this study proposes an algorithm based on evolutionary clustering and density clustering to detect the structure of dynamic communities. Finally, this study compares the proposed method with the classic method in the artificial network and the real network and analyzes the performance of the research model through data analysis. The research results show that the model constructed in this paper has good performance. Show more

Keywords: Neural network, network characteristics, ecological constraints, farmers, poverty alleviation

DOI: 10.3233/JIFS-189250

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Xiaozhou, Yang | Fan, Bai | Jones, Paul

Article Type: Research Article

Abstract: Based on the impact of epidemic prevention and control, the floating population supervision department classifies and controls the floating population by industry. There are many personnel management and control points. When the computer-aided management system is used, the outdoor environment is complex and the data interference is large. Therefore, the recognition accuracy of outdoor scenery is required to be higher. In this paper, a convolutional neural network with adaptive weights is proposed. In this method, the feature fusion strategy is combined with the network, and the optimal feature weight is obtained by training the network. In addition, this paper uses …multiple two classifiers instead of multiple classifiers to achieve accurate target classification. Experiments show that the method proposed in this paper has excellent performance in the detection of similar objects. The strategy of replacing multi classification network with multi classification network improves the accuracy and recall of target detection in known environment. Show more

Keywords: Adaptive weight, convolution neural network, fusion strategy, outdoor environment recognition

DOI: 10.3233/JIFS-189272

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Wenming, Huang

Article Type: Research Article

Abstract: The efficiency of traditional English teaching quality evaluation is relatively low, and evaluation statistics are very troublesome. Traditional evaluation method makes teaching evaluation a difficult project, and traditional evaluation method takes a long time and has low efficiency, which seriously affects the school’s efficiency. In order to improve the quality of English teaching, based on machine learning technology, this study combines Gaussian process to improve the algorithm, use mixed Gaussian to explore the distribution characteristics of samples, and improve the classic relevance vector machine model. Moreover, this study proposes an active learning algorithm that combines sparse Bayesian learning and mixed …Gaussian, strategically selects and labels samples, and constructs a classifier that combines the distribution characteristics of the samples. In addition, this study designed a control experiment to analyze the performance of the model proposed in this study. It can be seen from the comparison that this research model has a good performance in the evaluation of the English teaching quality of traditional models and online models. This shows that the algorithm proposed in this paper has certain advantages, and it can be applied to the practice of English intelligent teaching system. Show more

Keywords: Gaussian process, machine learning, English, teaching quality, evaluation model

DOI: 10.3233/JIFS-189233

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Sun, Changxin | Ma, Di

Article Type: Research Article

Abstract: In the research of intelligent sports vision systems, the stability and accuracy of vision system target recognition, the reasonable effectiveness of task assignment, and the advantages and disadvantages of path planning are the key factors for the vision system to successfully perform tasks. Aiming at the problem of target recognition errors caused by uneven brightness and mutations in sports competition, a dynamic template mechanism is proposed. In the target recognition algorithm, the correlation degree of data feature changes is fully considered, and the time control factor is introduced when using SVM for classification,At the same time, this study uses an …unsupervised clustering method to design a classification strategy to achieve rapid target discrimination when the environmental brightness changes, which improves the accuracy of recognition. In addition, the Adaboost algorithm is selected as the machine learning method, and the algorithm is optimized from the aspects of fast feature selection and double threshold decision, which effectively improves the training time of the classifier. Finally, for complex human poses and partially occluded human targets, this paper proposes to express the entire human body through multiple parts. The experimental results show that this method can be used to detect sports players with multiple poses and partial occlusions in complex backgrounds and provides an effective technical means for detecting sports competition action characteristics in complex backgrounds. Show more

Keywords: SVM, sports competition, visual system, simulation

DOI: 10.3233/JIFS-189224

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020