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

Authors: Yang, Qianru | Cheng, Shouming | Zhou, Bo

Article Type: Research Article

Abstract: In view of the weak vertical bearing capacity and low safety performance of the traditional soft rock pile foundation for human settlements, this paper proposes to monitor the vertical bearing capacity of the soft rock pile foundation for human settlements in Lhasa. The vertical mechanism of soft rock is analyzed, including the uniaxial compressive strength of rock around the pile, the relative displacement of pile rock and the interface condition of pile rock. The vertical bearing capacity of the pile foundation in soft rock is calculated by load transfer method. The side friction model and the pile end of the …pile are established to determine the pile foundation. The calculation formula of the load settlement curve is obtained by using the side friction model and the pile end resistance model. The vertical bearing capacity of the pile foundation in soft rock is analyzed when the pile side rock is in the elastic stage and the surrounding rock is in the plastic stage. The test results show that friction pile plays an important role in the test pile under the working load. This method can effectively monitor the vertical bearing capacity of pile in the soft rock geological environment of human settlements, and can be applied to practical projects. Show more

Keywords: Lhasa, human settlements, soft rock, geological pile foundation, vertical, bearing capacity

DOI: 10.3233/JIFS-179834

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

Authors: Tian, Chenxiao | Zhang, Baoshuai | Duan, Jun

Article Type: Research Article

Abstract: Based on the Copula-CoVaR framework, the Beta-skew-t-EGARCH model is used to capture the leverage effect of financial assets, the thick tail distribution and the conditional skewness. Then, based on the standard deviation, this paper introduces the extreme value theory, combined with the Copula function and the CoVaR method which are used to measure the effect of China’s crude oil market on the risk spillover effects of domestic and international commodity markets, and reveals the impact of China’s crude oil market. The results show that, regardless of the domestic Crude oil market and international commodity market, domestic crude oil market and …domestic commodity market, there is a two-way positive risk spillover effect, which shows asymmetric characteristics. The results provide some theoretical supports for the regulatory authorities to enhance the marketization level of China’s crude oil market, some suggestions for the investment institutions to assess the risk level of China’s crude oil market, and some reference value for investors to invest in China’s crude oil market. Finally, based on the conclusions of the study, this paper provides some targeted recommendations to the development of China’s crude oil market. Show more

Keywords: Oil markets, commodity markets, risk spillover effect

DOI: 10.3233/JIFS-179837

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

Authors: Ma, Liang | Gu, Jinan | Saeed, Tareq

Article Type: Research Article

Abstract: Gradually, OLED all screen has become one of mainstream mobile display devices. In this technology, the metal wiring in the bending area is prone to breakage, thus forming dead pixels. The yield rate may be affected by it. Therefore, the stress-strain analysis for the bending area in the bending process has become one of the main problems in OLED research. Firstly, the structural characteristics of OLED were analyzed, and the bending technology was introduced and analyzed. Secondly, the test process of discrete element method was analyzed. Finally, the strain analysis model was established through the multi-layer stacking characteristics of bending …area. Moreover, the simulation of bending process was completed by quasi-static analysis. Then, the validity of analysis was verified by the test comparison. The results show that the proposed method can not only analyze the mechanical properties of OLED bending area effectively under different cover plate stiffness, and the maximum error rate of the method is only 4.87, which is far lower than the traditional method. Therefore, the content and conclusion provide the further research of mechanical properties of OLED bending area with an important technical foundation. Show more

Keywords: Relaxation method, OLED, Newton’s second law, stress analysis

DOI: 10.3233/JIFS-179826

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

Authors: Liu, Qiang | Lian, Zhifeng | Guo, Yu | Yang, Feixue

Article Type: Research Article

Abstract: Combined with the relevant theories and frameworks, this study constructs evaluation indicator and index system of organization quality specificity immune evolution ability. On the basis, this study uses the intuitively fuzzy multi-attribute decision making method based on evidential reasoning to carry out empirical analysis of organizational quality specificity immune evolution ability, empirical analysis data derive from the research objects of relevant experts, typical and representative large-sized manufacturing enterprises. The empirical analysis results indicate that the intuitively fuzzy multi-attribute decision making method based on evidential reasoning considers subjective and objective factors, which integrates the intuitively fuzzy information and gives out the …corresponding decision according to the evaluation value. It is also useful, effective, feasible and operable to take the intuitively fuzzy multi-attribute decision making method based on evidential reasoning to evaluate, select and make decision choice on the best and optimal partner and investee object in multi-attribute group decision making according to organization quality specificity immune evolution ability, and give out orders of all partners and investees. The research methods and results can further improve the organization quality specificity immune efficiency, identify organization quality problems and defects, improve organization quality performance, and maintain organization health, which also provide new decision-making method for the multi-attribute groups of organization quality specificity immune evolution ability. Show more

Keywords: Intuitively fuzzy multi-attribute group decision making, evidential reasoning, organizational quality specificity immune evolution ability

DOI: 10.3233/JIFS-179832

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

Authors: Alzubi, Jafar A. | Jain, Rachna | Kathuria, Abhishek | Khandelwal, Anjali | Saxena, Anmol | Singh, Anubhav

Article Type: Research Article

Abstract: The paper presents a Collaborative Adversarial Network (CAN) model for paraphrase identification, which is a collaborative network holding generator that is pitted against an adversarial network called discriminator. There has been tremendous research work and countless examinations done on sentence similarity demonstration. Learning and identifying the constant highlights, specifically in various areas and domains is the main focus of paraphrase identification. It Involves the capture of regular highlights between two sentences and the community-oriented learning upon traditional ill-disposed and adversarial learning for common feature extraction. The model outperforms the MaLSTM model, which is the baseline model, and also proves to …be comparable to many of the state-of-the-art techniques. Show more

Keywords: Paraphrase identification, text classification, adversarial networks, LSTM, NLP

DOI: 10.3233/JIFS-191933

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

Authors: Dai, Songsong

Article Type: Research Article

Abstract: The symmetric implicational methods for fuzzy reasoning characterizes the solution B * (A * ) of the formula (A  → 1 B ) → 2  (A *  → 1 B * ) for the fuzzy modus ponens (fuzzy modus tollens), where →1 and →2 are two different implications. In this study, we provide a predicate formal representation of the solution for the symmetric implicational methods based on the LΠ formal logic system, including detailed logic proofs. We bring the symmetric implicational methods within a logical framework and provide a sound logic foundation for the symmetric implicational methods of fuzzy reasoning.

Keywords: Fuzzy reasoning, symmetric implicational method, LΠ logic

DOI: 10.3233/JIFS-191998

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

Authors: Hu, Jun-ming | Zhang, Yan-ru | Xu, Gang | Zhang, Zhi-qiang

Article Type: Research Article

Abstract: This paper has investigated hydrodynamic performances of biomimetic flapping foils based on RANS method, and numerical results of aero foil profile of NACA are verified. Besides, propulsion performances of six types of biomimetic flapping foils with pure rolling motion are compared. The influence of phase difference and moving amplitude of rolling and pitching composite motion on propulsion performance is researched and the change of wake stream field is analyzed. The results show that the hydrodynamic performance of bionic humpback whale flapping foil is better, whose average thrust in one cycle and the maximum propulsive efficiency increase with the increasing flapping …frequency; the propulsion performance of rolling and pitching composite motion is superior to that of pure rolling motion, and its better values of phase difference and moving amplitude are respectively 90° and 6°; the leading edge vortex appears two times in one cycle, consistent with the instantaneous thrust numerical results. This method provides a reference value for the design and application of AUV. Show more

Keywords: RANS method, biomimetic flapping foils, rolling motion, rolling and pitching composite motion, hydrodynamic performance

DOI: 10.3233/JIFS-179827

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

Authors: Hu, Ziyu | Ma, Xuemin | Sun, Hao | Yang, Jingming | Zhao, Zhiwei

Article Type: Research Article

Abstract: When dealing with multi-objective optimization, the proportion of non-dominated solutions increase rapidly with the increase of optimization objective. Pareto-dominance-based algorithms suffer the low selection pressure towards the true Pareto front. Decomposition-based algorithms may fail to solve the problems with highly irregular Pareto front. Based on the analysis of the two selection mechanism, a dynamic reference-vector-based many-objective evolutionary algorithm(RMaEA) is proposed. Adaptive-adjusted reference vector is used to improve the distribution of the algorithm in global area, and the improved non-dominated relationship is used to improve the convergence in a certain local area. Compared with four state-of-art algorithms on DTLZ benchmark with …5-, 10- and 15-objective, the proposed algorithm obtains 13 minimum mean IGD values and 8 minimum standard deviations among 15 test problem. Show more

Keywords: Many-objective optimization, evolutionary algorithm, Gaussian mixture model, selection mechanism

DOI: 10.3233/JIFS-192124

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

Authors: Tang, Ning

Article Type: Research Article

Abstract: In order to further improve the students’ learning ability, discrete analysis of linguistic pseudo-parallel constructions and symbols under the activation diffusion model is performed. Taking English as an example, this paper analyzes the usage of false paratactic construction from the perspectives of violating the restriction rules of paratactic structure and the irreplaceable nature of “and”; briefly introduces the discreteness of English vocabulary and analyzes the metaphorical function of the cognitive mode of lexical discreteness. Based on the improved activation diffusion model, the experiment class uses the activation diffusion model to implement the false parallel construction and vocabulary discrete teaching, while …the control class uses the traditional method to implement the false parallel construction and vocabulary discrete teaching. The final results show that the average English score of the experiment class is improved by 14.5%, while the control class is only improved by 3.2%. The results show that the activation diffusion model is helpful to grasp the pseudo paratactic construction and analyze the discreteness of English vocabulary. Show more

Keywords: Activation diffusion model, language, pseudo paratactic construction, symbol, vocabulary, discreteness

DOI: 10.3233/JIFS-179823

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

Authors: Wang, Hui | Cao, Zijian | Hong, Bo

Article Type: Research Article

Abstract: Intrusion detection systems (IDSs) play an important point in resisting hacker intrusion. With the rapid development of the network technology, network security has received more and more attention from researchers of different fields, and the traditional network security system based on the regular intrusion detection rules cannot meet the growing demand of changeable and timely intrusion prevention. Therefore, the development of efficient IDSs always is an open challenge. Firstly, a novel intrusion detection method based on the Convolutional Neural Network (CNN) is proposed in this paper. Secondly, based on the proposed method, an efficient, real-time and automated intrusion detection system …named IDS-CNN is well designed. The system is built by several open source tools, such as the packet capture interface Tcpdump, the traffic analysis Bro and the machine learning interface Tensorflow. The system is composed of data preprocessing, neural network training, network testing and intrusion response based on Linux platform. Finally, through the simulation experiment with NSL-KDD data set and the actual network flow test, the experimental results indicate that the proposed IDS-CNN system can not only complete the intrusion detection for network data streams efficiently, but also its detection precision is better than the state-of-the-art method. Show more

Keywords: Convolutional Neural Network, intrusion detection, NSL-KDD, data flow analysis

DOI: 10.3233/JIFS-179833

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

Authors: Zhou, Qinghong

Article Type: Research Article

Abstract: Aiming at the problem that Separable Gabor filter can destroy the ridge structure of fingerprint adjacent singular points, and the effect of directional Fourier filter in repairing fingerprint ridges is not obvious, a method for singular point region enhancement of fingerprint image based on symmetric phase consistency is proposed. Fingerprint image is preprocessed to extract effective fingerprint region; the singularity region of the effective fingerprint region is obtained by using the singularity extraction method; the method of singular region feature extraction is used to obtain the singular region feature of fingerprint image; the fuzzy clustering algorithm is used to enhance …the singular region feature of fingerprint image, which can enhance the singular region of fingerprint image. The results show that the quality of fingerprint image enhanced by the proposed method is better, the performance of denoising is remarkable, and the efficiency of extracting singular feature of fingerprint image is high. Show more

Keywords: Symmetric phase, consistency, fingerprint, image, singular point, enhancement

DOI: 10.3233/JIFS-179836

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

Authors: Zhou, Yuebin | Xu, Jianlong

Article Type: Research Article

Abstract: When resources are limited and the perception tasks are time-constrained, if multiple perception tasks request the response at the same time, it is easy to cause scheduling deadlocks in the perception layer and affect its access speed and perception efficiency. This paper studies the mathematical feature expression method of task and resource allocation when deadlock occurs in the perception layer. According to the conditions of deadlock mutual exclusion, non preemption, request and hold, cycle waiting, a deadlock detection model of hierarchical scheduling system based on time constraints is adopted to establish the time constraint relationship of the deadlock detector and …the genetic algorithm is applied to solve the problem of multi-tasks deadlock relieving strategy optimization in the perceptive layer. The research results and simulation experiments show that the deadlock relieving optimization method based on genetic algorithm can quickly relieve the deadlock, ensure the minimum cost of relieving, and significantly improve the efficiency of deadlock relieving. Show more

Keywords: Internet of things, perception layer, information scheduling, deadlock relieving

DOI: 10.3233/JIFS-179824

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

Authors: Li, Chunhua | Xu, Baogen | Huang, Huawei

Article Type: Research Article

Abstract: The adequate analysis of bipolar information of a semigroup using a fuzzy set requires incorporation of a bipolar fuzzy set and an appropriate semigroup structure. Motivated by studying partial order and lattice of bipolar fuzzy sets, and algebraic framework of bipolar fuzzy sets, in this paper, we introduce the notion of a bipolar fuzzy abundant semigroup by developing a new technique for constructing fuzzy semigroups. After obtaining some properties of bipolar fuzzy abundant semigroups, we give necessary and sufficient conditions of a bipolar fuzzy subset of an abundant semigroup to be bipolar fuzzy abundant. As an application, we extend our …results to the case of regular semigroup. In particular, bipolar fuzzy regular semigroups are investigated. Show more

Keywords: Bipolar fuzzy set, bipolar fuzzy abundant semigroup, good homomorphism, regularity condition, bipolar fuzzy regular semigroup, 20M20

DOI: 10.3233/JIFS-190951

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

Authors: Liu, Haiming

Article Type: Research Article

Abstract: In order to solve the problem that the seeder operated by hand controller lacks high-precision visual function, cannot self-identify the seed target, and has low sowing precision, this paper proposes a new automatic sowing robot control research based on basketball motion capture. Through motion capture, obtain the target characteristics. Based on the target characteristics acquired by the vision module of the robot, the path planning of the robot is realized by rotating a certain parking space Angle on the basis of real-time positioning. The performance test shows that the accurate recognition rate is higher than 95.2%, and the maximum is …98.1%. The accurate seed localization rate was 95.5% and the maximum was 98.2%. By comparing the trajectory precision of the joint space of the auto-seeding robot, the precision of the trajectory control method is better than that of the traditional method. The residual removal rate of this method is 39.87% – 46.25%. The effect of different placement methods on seed placement depth showed that the average depth value obtained by this method was 0.001.49, and the depth variation coefficient was 0.70% – 2.00%. This method can improve the target recognition rate and positioning accuracy, meet the needs of high precision sowing operations, and increase the crop yield. Show more

Keywords: Basketball motion capture, automatic seeding robot, multimedia database, feature extraction, path planning

DOI: 10.3233/JIFS-179820

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

Authors: Li, Jingjing

Article Type: Research Article

Abstract: In order to solve the problem of poor simulation accuracy of the traditional method for the coupled vibration of high-speed railway track, a discrete element simulation method for the coupled vibration of high-speed railway track under load is proposed. Based on the coupled vibration equation of high-speed railway track, the coupled vibration equation of high-speed railway track is built on the basis of determining the vector and parameters. The discrete element model is used to analyze the coupled vibration of high-speed railway track under the action of load, and the results of the discrete element simulation experiment of the coupled …vibration of high-speed railway track are obtained. In order to verify the simulation accuracy of the proposed discrete element method, a comparative experiment is designed. According to the experimental results, the proposed discrete element simulation method for coupled vibration of high-speed railway track under load greatly improves the simulation accuracy. In the 100th experiment, the simulation accuracy of this method is as high as 93%. The coupling vibration discrete element simulation method has better simulation effect. Show more

Keywords: Load, high speed railway, coupling vibration, discrete element simulation

DOI: 10.3233/JIFS-179822

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

Authors: Meng, Hua | Wang, Weixin

Article Type: Research Article

Abstract: The research on carbon footprint of steel energy supply chain plays an important role in energy conservation and emission reduction. Therefore, this article puts forward a definition method of carbon footprint of iron and steel energy supply chain based on correlation dispersion degree. Firstly, the definition of carbon footprint was given, and the carbon emission of iron and steel industry was calculated. On this basis, the influencing factors were analyzed quantitatively. Meanwhile, the carbon footprint data was processed based on carbon footprint accounting standards, including the carbon footprint data preprocessing, transformation and reduction. According to the preprocessing results, the computation …of carbon footprint was checked. Finally, the correlation dispersion degree of carbon footprints in the steel energy supply chain was analyzed, so as to achieve the definition of carbon footprints in the steel energy supply chain. In order to test the validity and feasibility of the proposed method, a simulation was carried out. Simulation results show that the result of the proposed method is close to the actual result, so that the proposed method can accurately get the influence of various factors on CO2 emissions of the steel industry, and thus to present some targeted measures to reduce the carbon emission of steel industry. Show more

Keywords: Carbon footprint, supply chain, data preprocessing, accounting

DOI: 10.3233/JIFS-179814

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

Authors: Yue, Guang | Pan, Yutian

Article Type: Research Article

Abstract: As the large error and low efficiency of manual tillage, tractor tillage has become the focus of the current research. However, tractor driving requires a lot of manpower and time. Therefore, the overall efficiency of agricultural tillage is reduced. To address this problem, an intelligent control system of agricultural unmanned tractor tillage trajectory based on machine vision is proposed in this paper. First, the hardware of the automatic control system of agricultural unmanned tractor is designed. Then the intelligent control algorithm is proposed to realize the software design, and the image of tractor tillage environment is processed. Finally, the adaptive …path tracking algorithm is applied to realize the adaptive tracking of the agricultural unmanned tractor tillage trajectory, so as to realize the trajectory control. Experimental results show that the designed system can accurately track and control the agricultural unmanned tractor tillage trajectory and improve tractor operation efficiency. Show more

Keywords: Machine vision, unmanned, agricultural tractor, intelligent control algorithm

DOI: 10.3233/JIFS-179818

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

Authors: Zhao, Di

Article Type: Research Article

Abstract: Due to poor noise elimination effect and low detection accuracy in traditional methods, a method to detect DC power disturbance data for charging piles based on linear algebra was presented. Firstly, a filter was constructed based on the mathematical morphology theory of linear algebra to preprocess the disturbed waveform, so as to filter out the random noise and impulse noise in signal. Secondly, the filtered waveform was analyzed according to the change rule of grid. And then, a simple and fast singularity detection criterion was proposed to detect the disturbance accurately and quickly and thus to locate the time. According …to the location result, the clustering algorithm based on GK was used to identify various types of disturbance data, so as to make countermeasures. Finally, voltage sag, voltage swell, harmonic wave and the combined disturbances were used to verify the proposed method. The experimental results show that the maximum denoising result of this method is 37.3, and the maximum detection accuracy of disturbance data is 0.952, which is much higher than the traditional method. The results show that the signal-to-noise ratio is larger and the detection effect is better based on the proposed method, so that the Intersection-over-Union (IoU) is improved and the detection accuracy is better. In conclusion, the overall detection performance is better. Show more

Keywords: Mathematical morphology, GK clustering algorithm, signal recognition, SNR

DOI: 10.3233/JIFS-179828

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

Authors: Liu, Qiang | Lian, Zhifeng | Guo, Yu

Article Type: Research Article

Abstract: Quality is of great significance in enterprises, strengthening and identifying enabling factors of quality defect management are one of core goals of organizational operation management. In this study, sense-making theory is adopted to identify organizational quality defect management enabling factors, and interval-valued hesitant fuzzy set ELECTRE for multi-attribute decision-making method and quantile regression analysis method are used to empirically identify and verify organizational quality defect management enabling factors, revealing influence size and scale, influence degree and influence significance level of enabling factors on organizational quality defect management. Empirical analysis results indicate that combination methods of sense-making theory, interval-valued hesitant fuzzy …set ELECTRE for multi-attribute decision-making method and quantile regression analysis method can effectively identify organizational quality defect management enabling factors, which will have great promise in the field of organizational quality management and operation management based on the rationality, feasibility and applicability. Show more

Keywords: Interval-valued hesitant fuzzy set ELECTRE for multi-attribute decision-making, organizational quality defect management, quantile regression method, sense-making theory

DOI: 10.3233/JIFS-179831

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

Authors: Li, Jinghong | Wang, Qiang

Article Type: Research Article

Abstract: In the past, in the process of tracking and controlling the discretely-actuated manipulator, the tracking result has a large error. To this end, a control system of trajectory tracking of discretely-actuated manipulator based on computed torque method was designed. The overall framework of the system was analyzed and designed, and the hardware of the system was designed in an integrated DSP information processing environment. The design of the monocular stereo sensor, drive controller, servo drive, etc. was described in detail. Then the control algorithm, the computed torque method, was analyzed. Finally, with the help of the control platform of discretely-actuated …manipulator, the control system of trajectory tracking of discretely-actuated manipulator based on computed torque method was verified. After the different control algorithms were added, the trajectory tracking accuracy of the discretely-actuated manipulator was compared. The experimental results show that the maximum errors of each joint in the system are 0.0568 rad, 0.0347 rad and 0.0044 rad, which are lower than the traditional system, it is shows that the reliability of the system is verified. Show more

Keywords: Monocular stereo sensor, drive controller, servo driver, calculation moment method

DOI: 10.3233/JIFS-179829

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

Authors: Ren, Chang’an | Luo, Qingyun | Zhao, Jinguo | Huang, Yinzhen

Article Type: Research Article

Abstract: For the problem of slow scheduling speed and poor load balancing of agricultural information resource scheduling in the current cloud computing, an agricultural information resource scheduling algorithm based on firefly algorithm is proposed in this paper. In cloud computing, according to the idea of earliest completing resource scheduling and using the least cost, the agricultural information resource scheduling model with time constraint is constructed. The minimum completion time and scheduling cost of resource scheduling are determined and the objective function of resource scheduling is built. The chaos algorithm is used to optimize the firefly algorithm to solve the objective function …and improve the convergence speed of resource scheduling. Agricultural information resource scheduling is achieved according to the convergence results and by using Lagrangian relaxation function. Experimental results show that the proposed algorithm is faster in scheduling agricultural information resources and higher in load balancing. Show more

Keywords: Cloud computing, firefly algorithm, agricultural information, resource scheduling

DOI: 10.3233/JIFS-179817

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

Authors: Xiong, Qianli

Article Type: Research Article

Abstract: The traditional spoken English semantic recognition model requires a hand-made pronunciation dictionary and a predefined alignment between audio and phonemes, so the recognition is not good. In order to improve the efficiency of spoken English semantic recognition, this study studies the colloquial semantic feature recognition method of English colloquial database under the framework of machine learning, and then studies the semantic recognition of spoken English based on the results of Chinese name recognition. Moreover, this study has carried out a detailed analysis of the traditional speech recognition system, introduced the preprocessing and feature extraction of speech, traditional acoustic models, language …models, decoding search and dictionary, etc., which covers the components necessary for the traditional speech recognition system. In addition, this study further analyzes the basic theory of acoustic models and improves the model. Finally, this study designed a controlled trial to perform a performance analysis of the model. The analysis of the experimental results shows that the English spoken language semantic recognition model proposed in this study has a significant improvement over the traditional speech recognition system. Show more

Keywords: Pronunciation rules, spoken English, semantic recognition, feature analysis, simulation model

DOI: 10.3233/JIFS-179808

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

Authors: La, Meixiang

Article Type: Research Article

Abstract: Sea-buckthorn, with high economic value, is one of the important tree species for windbreak, sand fixation and conservation of water and soil. Based on this, an equilibrium analysis method for ecological and economic benefits of sea-buckthorn was proposed. After analyzing the ecological function and economic value of sea-buckthorn, based on the system theory, the utilization benefit equilibrium model of sea-buckthorn was constructed from economy and ecology two dimensions. The equilibrium of sea-buckthorn utilization benefit in an evolutionary cycle was divided into low-level symbiosis, coordinated development, limit development and regeneration development four stages. In order to comprehensively reflect the overall situation …of sea-buckthorn utilization benefits, an index system including two major systems of social economy and ecological environment was designed, and 12 indicators in the ecological function and economic value analysis results of sea-buckthorn were selected to judge the interaction balance between economic benefits and ecological benefits. Taking Liaoning Province as the research object, the comprehensive economic and ecological benefits of sea-buckthorn utilization between 2004 and 2017 shows that during this period, the growth rate of ecological benefits was slower than that of economic benefits and had fluctuations. From the evolution curve of the equilibrium of utilization benefits, the sea-buckthorn in Liaoning Province is in the coordinated development stage, but the coupling degree has been increasing in recent years, indicating that the utilization benefits of sea-buckthorn in Liaoning Province may enter the limit development stage. According to the research results, this method can effectively analyze the balance of ecological and economic benefits of sea-buckthorn, which is conducive to the maximum value of sea-buckthorn. Show more

Keywords: System theory, liaoning province, index system, weight, entropy weight method

DOI: 10.3233/JIFS-179816

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

Authors: Anxie, Tuo | Bing, Li

Article Type: Research Article

Abstract: The deep learning architecture consists of multiple layers of non-linear computing units, and the output of each lower layer is used as the input of the higher layer, which can learn effective feature representations from a large amount of input data. In this paper, the author analyze the application of deep learning and artificial intelligence in the psychological mechanism of language activity. Language activity is a complex cognitive process that drives the comprehensive response, coordination, and operation of body-related functions. In this activity, there are three information processing links: language input, intermediate processing and language output. Intermediate processing is the …core part. Information processing drives systemic language responses, including those of the oral muscles and nervous system. According to the experimental results, we analyze the psychological factors in the processing of language activity information, study the language processing and information processing modes of deep learning and artificial intelligence in the brain, and the psychological mechanism of English-Chinese alternate language activities. the result predicted by SVM regression is 5.35 m/s, and the prediction error is 4.5%. In addition to the speed prediction, we used the same sample data to predict the direction of the next second. The simulation results this system can predict the language activity. Show more

Keywords: Deep learning, artificial intelligence, language activities, algorithm simulation

DOI: 10.3233/JIFS-179806

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

Authors: Gong, Jianhu

Article Type: Research Article

Abstract: Aiming at the problem of plaintext recovery attack on 3DES algorithm with different byte keys, a plaintext recovery method for 3DES algorithm with different byte keys is proposed. In order to strengthen the anti-attack ability of DES algorithm, 3DES algorithm is used, which includes double-key 3DES of and triple-double-key 3DES. The 3DES algorithm with different seed key length is used to recover the plaintext. The attack algorithm for the first 256-byte plaintext encrypted by 3DES algorithm are given through the single byte deviation rule and double byte deviation rule. The results show that with the increase of the corresponding quantization …order, the processing effect of the method is better than that of the chaos mapping method (4.2 dB), and with the increase of the quantization order, the advantage of the method is constantly improved; the attack result of the method on 256 plaintext is shown as the 114th byte to 127th byte from 3072 bytes, so that in practical application, the plaintext encrypted by 3DES algorithm can be recovered better. Show more

Keywords: Different bytes, key, 3DES algorithm, plaintext, recovery, chaotic key

DOI: 10.3233/JIFS-179821

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

Authors: Zhang, Hui

Article Type: Research Article

Abstract: From the current situation, it can be seen that there are certain deficiencies in the current models of spoken English analysis. In order to improve the English spoken analysis effect, this study builds an English spoken analysis model based on transfer learning and analyzes the performance of spoken English recognition. In order to make full use of the characteristics of speech feature modes to compensate for the shortcomings of single mode in speech recognition, this paper proposes a multimodal shared speech feature learning method, that is, multimodal shared speech feature learning method based on locality, sparsity, and identifiable typical correlation …analysis. The method introduces locality, sparsity and discriminability, and the method effectively improves the English spoken recognition effect to a certain extent. In addition, this paper designs a controlled experiment to analyze the performance of the system model. The research results show that the algorithm has certain effects and can be applied to practice. Show more

Keywords: Transfer learning, spoken English, speech recognition, system model, feature analysis

DOI: 10.3233/JIFS-179811

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

Authors: Yang, Yi

Article Type: Research Article

Abstract: Smart communities are the main content of smart city construction and a microcosm of urban smart management. Its construction has developed with the advancement of technology. The smart community contains various refined smart scenarios, involving various smart hardware and smart system ecological chain construction. This paper analyze the smart community security monitoring based on artificial intelligence and improved machine learning algorithm. In the deployment of urban surveillance, a smart camera embedded with face recognition technology can transmit facial feature data to a computer center database through a computer network while taking a suspicious portrait, and the system can automatically integrate …the facial database of fugitives compared quickly and accurately. Simulation results show that the artificial intelligence mode can effectively improve the accuracy of facial recognition, and at the same time, it is effective for dynamic image monitoring of moving objects. The size of the detected interest point will be reduced by more than 30%, which reduces the calculation amount to some extent and improves the decision efficiency. Show more

Keywords: Artificial intelligence, community security identification, smart community, image detection

DOI: 10.3233/JIFS-179809

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

Authors: Hong, Wang | Peng, Yue

Article Type: Research Article

Abstract: The intelligent traffic dispatch delay control system is an application system that combines system integration and command dispatch, and system integration serves command dispatch. This system has relatively independent system functions and various research results obtained from multi-data source analysis. Therefore, it is advisable to adopt a technical route of functional modularization and multi-layered architecture. Each functional module relatively completes the required functions independently, and provides a hierarchical service relationship between the modules. Maximizing the efficiency of road use is an important part of urban road traffic control. Urban road traffic control is mainly the control of traffic signals. Simulation …results show that this system can effectively improve the efficiency of traffic dispatching, and at the same time has a real-time feedback function. The shortest path can be calculated through vehicle monitoring and combined with the GIS module. The vehicle position information and the shortest path between each vehicle and the accident point are displayed in the map panel, and the operator selects a vehicle to be dispatched according to a vehicle selected on the map and associated with a row in the vehicle information panel table. Show more

Keywords: Dispatching system, intelligent transportation, delay control system, deep learning

DOI: 10.3233/JIFS-179807

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

Authors: Wang, Ping

Article Type: Research Article

Abstract: In order to improve the safety of building structure, the discrete element method is introduced to test the stability of building concrete structure. Taking reinforced concrete as the research object and using Mohr-Coulomb criterion as the concrete failure criterion, determine the stiffness coefficient, damping coefficient and time step of reinforced concrete. Simulation of failure modes of reinforced concrete beams under different shear-span ratios. Determining the collapse process of reinforced concrete structure under the action of strong earthquake El-Centro north-south wave, and testing the stability of reinforced concrete structure. The results show that at the moment of 3.25 s, the bottom spring …of the bottom column of the frame structure is damaged, and the upper end of the right column of the middle two layers is deformed and damaged. At this moment, the frame structure collapses. As the shear-span ratio increases, the failure mode of reinforced concrete beams evolves in the order of diagonal pressure, shear pressure and cable tension. Its shear strength is gradually weakened, and the proposed method can effectively simulate the stability of concrete structures under the action of earthquakes and collapse. Show more

Keywords: Discrete element method, buildings, concrete structure, failure criterion, collapse, stability detection

DOI: 10.3233/JIFS-179815

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

Authors: Yu, Weiqing | Huang, Zhichao | Zhong, Chengping | Liu, Juping | Yuan, Zhensong

Article Type: Research Article

Abstract: In order to solve the problem of low efficiency and low efficiency of traditional methods, a method based on discrete wavelet is proposed to suppress the torsional vibration noise of automobile transmission system. Based on the operation mechanism of automobile transmission system, the transmission system model is built. In this model, the features of torsional vibration of transmission system were analyzed and the vibration signals were measured. The hardware equipments were used to collect the noise caused by torsional vibration, and then the discrete wavelet processing technology was used to quantify the torsional vibration noise. Based on the quantized noise …data, the torsional vibration noise of automobile driveline was suppressed by active suppression and passive suppression. The experimental results show that the suppression time of this method for different noise size is less than 0.5 s, far less than the traditional method. Experimental results prove that the designed noise suppression method can greatly reduce the torsional vibration noise, so it has good application effect. Show more

Keywords: Torsional vibration mechanics model, noise sampling, vibration signal, differential equation

DOI: 10.3233/JIFS-179830

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

Authors: Sabir, Zulqurnain | Amin, Fazli | Pohl, Daniel | Guirao, Juan L.G.

Article Type: Research Article

Abstract: In this research study, an advance computational intelligence paradigm is used for solving second order Emden-Fowler system (EFS) based on artificial neural network, genetic algorithm (GA) which is a famous global search method, sequential quadratic programming (SQP) known as rapid local refinement and the hybrid of GA-SQP. The proficiency of the designed scheme is inspected by solving the three examples of EFS to check the efficiency, consistency, precision and exactness of the technique. The numerical outcomes of the purposed scheme are compared with the exact solution that shows the significance of the scheme based on accuracy, correctness and convergence. Moreover, …statistical explorations have been executed to verify the precision and accuracy of the outcomes based on performance measures of mean absolute deviation, root mean squared error and variance account for. Show more

Keywords: Emden-Fowler system, artificial neural network, genetic algorithm, sequential quadratic programming, statistical analysis

DOI: 10.3233/JIFS-179813

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2020

Authors: Huang, Xiangrong | Xie, Ruhe | Huang, Lijuan

Article Type: Research Article

Abstract: To solve the problems of the traditional cold chain logistics management mode of agricultural products, such as loose circulation, inaccurate information transmission, untimely processing, serious loss of fresh agricultural products, a real-time and accurate management of cold chain logistics is established to study the real-time emergency management mode of cold chain logistics for agricultural products under the background of “Internet+”. Method: Under the background of “Internet+”, the e-commerce platform and the cold chain logistics network are combined, and the physical real-time emergency management mode of the cold chain of agricultural products is divided into the sub-mode of “production warehouse+cold chain”, …the sub-mode of “e-commerce+cold chain express+smart cabinet” and the sub-mode of “cold chain storage+chain new retail”; through the circulation efficiency improvement algorithm of cold logistics supply chain, the circulation loss between nodes is reduced, to improve the circulation efficiency of the supply chain; The evaluation method of real-time emergency management mode for cold chain logistics, the entropy weight method and the analytic hierarchy process are selected to jointly determine the weight, and the fuzzy comprehensive evaluation method is used to comprehensively evaluate the emergency management effect of cold chain logistics for agricultural product. Results: The final score of the performance evaluation in enterprise SX’s fresh agricultural product supply chain using the emergency management mode is 69.52 points, and the efficiency value of cold product logistics management in the enterprise C is 0.536. Conclusion: The real-time emergency management mode of cold chain logistics of agricultural products studied has certain feasibility, which can accurately analyze the advantages and disadvantages of cold chain logistics management of different enterprises. Show more

Keywords: Internet+, agricultural products, cold chain logistics, management mode, supply chain

DOI: 10.3233/JIFS-179819

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

Authors: Wei, Guiwu | He, Yan | Lei, Fan | Wu, Jiang | Wei, Cun | Guo, Yanfeng

Article Type: Research Article

Abstract: In recent years, with the increased voice for protecting the environment by the people all over the world, the governments also have actively adopted more and more measures to further promote environmental conservation and sustainable development. Traditional procurement approaches have not well updated to the current needs of the society, especially for the retail industry which is in relation to the national economy due to numerous products and different suppliers being involved. Therefore, the need for green procurement is more important. The qualified green supplier selection is the core of green procurement, which is the utmost importance in the business …competition throughout the supply chain in today’s strong business competition. Thus, in order to obtain the optimal green supplier, integration of Entropy weights and multi-attributive border approximation area comparison (MABAC) under uncertain probabilistic linguistic sets (UPLTSs) has offered a novel integrated model, in which information Entropy is utilized for calculating objective weights with UPLTSs to acquire the final ranking result of green supplier. Besides, so as to indicate the applicability of devised method, it is confirmed by a numerical case for green supplier selection. Some comparative studies are made with some existing methods. The proposed method can also serve for selecting suitable alternative successfully in other selection problems. Show more

Keywords: Multiple attribute group decision making (MAGDM), uncertain probabilistic linguistic term sets (UPLTSs), MABAC method, entropy method, green supplier selection

DOI: 10.3233/JIFS-191584

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

Authors: Xiaofeng, Du

Article Type: Research Article

Abstract: Modern information technology conforms to the development of the times. Now we live in an increasingly information, digital and network environment. This paper presents a design scheme of music assisted instruction system, which makes use of the features of intelligent chip, such as powerful function, high cost performance, deep learning and artificial intelligence algorithm with the advantages of global optimization, self-adaptive and fast, so that the system can objectively and quantificationally evaluate the result of each performance of the evaluated person. In order to use the advantages of simulated annealing algorithm, which can find the global optimal solution and fast …convergence speed, the standard track is divided into several key groups according to the music score, and the evaluation function is introduced for each key group. The improved algorithm MPRA has significantly improved the prediction accuracy in the online music learning knowledge base network. This shows that the improved algorithm is better than the original path sorting algorithm. However, in a network with a large average number of paths, the accuracy of link prediction is relatively lower, which indicates that the applicability of the weight value of the path has certain limitations. Show more

Keywords: Deep learning, artificial intelligence algorithm, multimedia music teaching, system design

DOI: 10.3233/JIFS-179800

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

Authors: Kesicioğlu, M. Nesibe | Şamlı, Esra

Article Type: Research Article

Abstract: In this paper, orders based on uni-nullnorms on bounded lattices are introduced and discussed. By this way, the existing orders in the literature induced by t-norms, t-conorms, uninorms and nullnorms are extended to much more general form. The relationships between the orders induced by uni-nullnorms and the orders induced by their underlying t-norms, t-conorms, uninorms and nullnorms are presented. A necessary and sufficient condition making a bounded lattice again a lattice with respect to the orders based on uni-nullnorms is given. Also, the relationships between the partially ordered sets based on the orders induced by t-norms and induced by their …N-dual t-conorms and conjugate t-norms, which are special uni-nullnorms, are investigated. Show more

Keywords: Uninorm, bounded lattice, partial order, uni-nullnorm

DOI: 10.3233/JIFS-191583

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

Authors: Hongfeng, Cui

Article Type: Research Article

Abstract: The information network itself has the characteristics of vulnerability, and the information network is facing more and more threats. The existence of these two factors is the main reason for the frequent discovery of information network security problems. Network security depends on the development of information technology. Only the independent and controllable technology can obtain a safe and stable development space. However, network security is the premise of the development of information technology, so we can’t go ahead blindly without considering the cost and cost for the development. In the face of safety and risk, we should master a balance …point, and take multiple measures such as management, technology and system to control the safety risk in a controllable range. This paper analzye the information network security construction based on depth learning and modulus algorithm. The improved algorithm can be stably controlled within 0.007s in training time. Moreover, as the training difficulty increases, the training time will gradually increase, but the change is not obvious, and the overall tends to be stable. By training neural network with the selected instance and make its maximum close to real system working model or network attack model, thus the input to any of its monitoring data to be able to make quite the right judgment. Show more

Keywords: Deep learning, fuzzy algorithm, intrusion detection, network security

DOI: 10.3233/JIFS-179799

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

Authors: Jingyu, Chen | Qing, Chen

Article Type: Research Article

Abstract: The reasonable ranking of web pages is an important step in the realization of search engine technology, and plays a key role in improving the information quality of high retrieval and presentation web pages. In this paper, the authors analyze the application of deep learning and BP neural network sorting algorithm in financial news network communication. According to the historical data of users in the process of searching and browsing, we can extract the potential connection between the information of the page itself and the user’s behavior habits, so as to mine the user’s potential preference page. Finally, we use …a variety of technologies to mix recommendation and sorting. By observing the effect of multiple training, it is found that the convergence speed of the network model is fast, the training time is short and the training effect is good. We need to fully understand the characteristics of financial news communication in the new media era, and then fully grasp people’s financial news reading habits on this basis, and then put forward the innovative mode of financial news communication in the new media era on the basis of these two points. Show more

Keywords: Neural network algorithm improvement, news dissemination, prediction model, network input

DOI: 10.3233/JIFS-179795

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

Authors: Ul Haq, Amin | Li, Jianping | Ali, Zafar | khan, Jalaluddin | Memon, Muhammad Hammad | Abbas, Muhammad | Nazir, Shah

Article Type: Research Article

Abstract: Accurate and efficient recognition of Parkinson’s disease is one of the prominent issues in the field of healthcare. To address this problem, different methods have been proposed in the literature. However, existing methods are lacking in accurately recognizing the Parkinson’s disease and suffer from efficiency problems. To overcome these problems faced by existing models, this paper presents a machine-learning-based model for Parkinson’s disease recognition. Specifically, a hybrid feature selection algorithm has been designed by integrating the Relief and ant-colony optimization algorithms to select relevant features for training the model. Moreover, the support vector machine has been trained and tested on …the selected features to achieve optimal classification accuracy. Additionally, the K-fold cross-validation technique has been employed for the optimal hyper-parameters value evaluation of the model.The experimental results on a real-world dataset, i.e., Parkinson’s disease dataset is revealed that the proposed system outperforms baseline competitors by accurately recognizing the Parkinson’s disease and achieving 99.50%accuracy on the selected features. Due to high performance is achieved our proposed method, we are highly recommended for the recognition of PD. Show more

Keywords: Relief, ant colony optimization, parkinson’s disease recognition, feature selection algorithm, classification, machine learning

DOI: 10.3233/JIFS-200075

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-21, 2020

Authors: Lin, Hongjie

Article Type: Research Article

Abstract: The goal of enterprise ERP is to select useful information and finally realize the goal of transforming information into enterprise competitiveness. At present, the research on the data quality optimization management of ERP system is not systematic enough, which can not achieve the effect of optimization management. In this paper, the author analyzes the enterprise ERP system optimization based on deep learning and dynamic fuzzy model. After dividing all kinds of typical activities of information process, this paper builds a model of information process of each ERP module with the method of information product diagram, which makes the invisible information …production process visible, so as to realize the continuous improvement of information quality, and provides a complete set of optimized management methods and measures for enterprise information quality. The simulation results show that it is feasible to use neural network to solve the optimization design of the system. The main reason is that the variables among neural networks are distributed in parallel, and when the energy function tends to be stable, it can reach its minimum value, so as to achieve the purpose of optimization. Show more

Keywords: Deep learning, neural network, enterprise ERP system, data quality optimization

DOI: 10.3233/JIFS-179790

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

Authors: Naeem, Khalid | Riaz, Muhammad | Afzal, Deeba

Article Type: Research Article

Abstract: The inspiration behind this article is to introduce the notions of fuzzy neutrosophic soft σ -algebra ( fns σ -algebra), fuzzy neutrosophic soft measure ( fns measure) and fns outer measure using the concepts of fuzzy sets, soft sets, neutrosophic sets and soft σ -algebra. A number of related results along with elaborative examples are also included. We render an algorithm based upon fns -mapping to deal with imprecise data utilizing mean proportional operator and employ it on multi-criteria group decision making (MCGDM) …problem to exhibit its efficacy. Show more

Keywords: 𝔉𝔑𝔖 σ-algebra, 𝔉𝔑𝔖-measure, 𝔉𝔑𝔖 outer measure, MCGDM

DOI: 10.3233/JIFS-191062

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

Authors: Khan, Waqar | Hila, Kostaq

Article Type: Research Article

Abstract:  We introduce the notion of fuzzy Abel-Grassmann’s hypergroupoid, hypercongruence, fuzzy hypercongruence, fuzzy strong hypercongruence, compatible relations in an Abel-Grassmann’s hypergroupoid. This paper is aimed to study fuzzy hyperideals, smallest fuzzy hyperideals, fuzzy equivalence relations, fuzzy compatible fuzzy strong compatible, fuzzy hypercongruences, fuzzy strong hypercongruences, fuzzy regular, fuzzy strong regular relations and fuzzy hypercongruences in Abel-Grassmann’s hypergroupoids. Characterizations of hypercongruences, their corresponding quotient structure, homomorphisms and an important theorem on embedding Abel-Grassmann’s hypergroupoids by means of fuzzy sets. We show that each hypergroupoid is embedded into a poe -hypergroupoid of all fuzzy subsets of an Abel-Grassmann’s hypergroupoid.

Keywords: Abel-Grassmann’s hypergroupoid, fuzzy equivalence relation, fuzzy hypercongruence, homomorphism, fuzzy strong hypercongruence, cartesian product, regular Abel-Grassmann’s hypergroupoid

DOI: 10.3233/JIFS-200277

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

Authors: Liang, Shufen | Chen, Chen | Zou, Guanhua

Article Type: Research Article

Abstract: The target detection and recognition module of traditional automatic driving system is vulnerable to the influence of the surrounding environment, which makes the system lack of accuracy and real-time. In this paper, based on the analysis of the traditional algorithm, the SVM method of intelligent control algorithm is used to optimize the existing vehicle automatic driving system. The optimization algorithm obtains the corresponding classifier model through the extraction and training of the input image features, and then uses the model to detect and recognize the target. The experimental results show that the optimized algorithm is much better than the traditional …feature-based automatic driving system target detection algorithm in detecting speed and accuracy. At the same time, the false alarm rate of detection also decreased, which fully verified the feasibility of the optimization method. Intelligent car driving technology greatly reduces the driver’s learning cost, and also reduces the workload of human brain. The continuous maturity of perception, communication and embedded technology will strongly support the development of intelligent vehicles. Combined with the active safety technology of auxiliary driving, such as adaptive cruise, vehicle approach notification, etc., it can make the intelligent vehicle driving more safe and reliable. Show more

Keywords: Computer vision, neural network, robot, intelligent driving system

DOI: 10.3233/JIFS-179803

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

Authors: Yu, Wen | Vega, Francisco

Article Type: Research Article

Abstract:  The data driven black-box or gray-box models like neural networks and fuzzy systems have some disadvantages, such as the high and uncertain dimensions and complex learning process. In this paper, we combine the Takagi-Sugeno fuzzy model with long-short term memory cells to overcome these disadvantages. This novel model takes the advantages of the interpretability of the fuzzy system and the good approximation ability of the long-short term memory cell. We propose a fast and stable learning algorithm for this model. Comparisons with others similar black-box and grey-box models are made, in order to observe the advantages of the proposal.

Keywords: LSTM, fuzzy neural networks, nonlinear system identification

DOI: 10.3233/JIFS-200491

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

Authors: Bo, Ren | Ming, Meng | Guangguo, LI | ping, Liu

Article Type: Research Article

Abstract: At present, most athletes’ motion recognition models still have certain problems, and relevant development is still in infancy. Moreover, the key issues mainly include the detection, tracking and identification of moving targets, and most of the technologies are not mature enough. In view of this, this study introduces the classification algorithm of support vector machine in detail on the basis of theory, which is in line with the statistical principle. At the same time, this paper uses the optimization theory to solve the optimal classification decision function, and finally gives its algorithm steps. The experimental results on the data set …prove that the proposed algorithm can achieve better classification results. Subsequently, this paper analyzes the basic theory of Kalman filter, and introduces the multi-target tracking algorithm combined with motion and apparent information. Finally, this paper combines experiments to analyze the performance of the algorithm. The research results show that the method proposed in this study has certain practical effects. Show more

Keywords: Machine learning, game scene, athletes, motion recognition

DOI: 10.3233/JIFS-179805

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

Authors: Bin, Zhang

Article Type: Research Article

Abstract: In the analysis of the dimension of economic development, the clustering method has a strong dependence on the selection of the central point. However, the random selection of the central point by the traditional K-means clustering method involves the most sensitive central point selection problem of the clustering method. In order to improve the economic development dimension analysis, this paper improves the initial center selection method based on the traditional K-means clustering method, so that the traditional K-means clustering method is no longer a random selection of initial center, and the problem of local optimal solution is also solved. At …the same time, the system operation reduces the number of clustering and iterations and improves the efficiency of the algorithm. In addition, this article uses an example to perform algorithm performance analysis. The results show that the proposed algorithm has certain effects and can provide theoretical reference for subsequent related research. Show more

Keywords: K-means clustering, nearest neighbor discrimination, economic development, regional economy, dimensional analysis

DOI: 10.3233/JIFS-179810

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

Authors: Wanni, Mo

Article Type: Research Article

Abstract: It is a very challenging task to develop a grammatical error correction model with many types of error correction and high accuracy of error correction for various English grammar mistakes. Based on Chinese English learners, this paper analyzes the grammatical mistakes that they often make, and then studies and implements an English grammar correction model with high precision and many types of error correction. Moreover, this study combines genetic algorithm and KNN algorithm to construct a smart English grammar recognition system. At the same time, on the basis of summarizing the work of predecessors, this paper, based on advanced theoretical …and technical knowledge, designs a grammatical error correction model based on rules and statistics. In addition, for the corresponding related word errors, this study proposes an error correction model of related word grammar. Finally, this study selects the features of artificially extracted English related words for error correction, and finally selects the optimal feature subset to improve the accuracy of model error correction. Show more

Keywords: Genetic algorithm, KNN algorithm, English, grammar, feature recognition

DOI: 10.3233/JIFS-179804

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

Authors: Xie, Mengying | Liu, Xiaolan | Pan, Gan

Article Type: Research Article

Abstract: Multi-view subspace clustering arises in many computer visional tasks such as object recognition and image segmentation. The basic idea is to measure the same instance with multiple views. In this paper, we proposed two centralized joint sparse representation models, namely, Centralized Global Joint Sparse Representation (CGJSR) and Centralized Local Joint Sparse Representation (CLJSR) for multi-view subspace clustering. CGJSR and CLJSR force the concatenated representation matrix of all views and the representation matrix of each view to be sparse respectively. Both CGJSR and CLJSR allow the sparse coefficient matrix to approach a unified latent structure with an acceptable error. Noises and …outliers regularization terms are included in CGJSR and CLJSR to reduce the influence of noises and outliers. Related optimization problems are solved using the alternating direction method of multipliers. Compared with seven state-of-the-art multi-view clustering algorithms, our proposed algorithms can achieve better or comparable results on four real-world datasets. Show more

Keywords: Sparse representation, feature fusion, multi-view subspace clustering

DOI: 10.3233/JIFS-192101

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

Authors: Wu, Jian | Feng, Qiuju

Article Type: Research Article

Abstract: If the online education platform simply presents offline course content and teaching resources, it will result in poor interaction between teachers and students and poor student learning efficiency because of the time and space barriers in distance education. At the same time, it has a one-way teaching for all students without any difference, so its personalization is poor. In order to improve the efficiency of network education knowledge recommendation, based on the traditional neural network, this study combines the actual needs of network education to construct an improved neural network-path sorting algorithm. Moreover, this study builds a network education knowledge …recommendation system based on the algorithm and explores the functions of each module of the system to realize all system functions. In addition, this study performs system function tests on a complete system. The results show that the proposed algorithm is higher than the traditional recommendation algorithm in recommendation effect and recommendation efficiency, and has certain practical effects, and can provide theoretical reference for subsequent related research. Show more

Keywords: Improved neural network, path sorting, network education, educational resources, personalized recommendation

DOI: 10.3233/JIFS-179787

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

Authors: Munirathinam, T. | Ganapathy, Sannasi | Kannan, Arputharaj

Article Type: Research Article

Abstract: Rapid introduction of new diseases and the severity improvement of existing dead diseases due to the bad food habits and lacking of awareness over the health conscious food items those are available in the market. The Internet of Things (IoT) gets more attention for reducing the disease severity by knowing the current status of their disease according to the dynamic inputs of human body through IoT devices today. Moreover, the combination of IoT and cloud computing technologies are playing major roles in e-health services. In this scenario, security is a major issue in the process of data storage and communication. …For this purpose, we propose a new e-healthcare system for monitoring the dead disease level by using the technologies such as IoT and Cloud with the help of deep learning approach and fuzzy rules with temporal features. In this system, the medical data is retrieved from various located patients who are utilizing the e-healthcare assisting devices. First, the retrieved and encrypted data is stored in cloud by applying a newly proposed secured cloud storage algorithm. Second, the stored data can be retrieved the data as original data by applying the decryption process. Third, a new cloud framework is introduced for predicting the status of heart beat rates and diabetes levels by using the medical data that is created by applying the UCI Repository dataset. In addition, a new deep learning approach which applies the Convolutional Neural Network for predicting the disease severity. The experimental results are obtained by conducting various experiments for the proposed model by using the dataset and the hospital patient records. The proposed model results outperforms the available disease prediction systems in terms of prediction accuracy. Show more

Keywords: Internet of things (IoT), CNN, cryptography, encryption, decryption, elliptic curve cryptography and e-healthcare.

DOI: 10.3233/JIFS-191490

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

Authors: Yan, Lixin

Article Type: Research Article

Abstract: In traditional teaching, people can quickly guess the emotion type of the other person based on facial expressions but understanding the human facial expression by computer is a very complicated problem. There may be some differences in the expression of each person. Therefore, how to make the computer ‘read and understand’ the emotional state of the person according to the facial expression of the person is the research focus of this paper. In this paper, the expression recognition based on dynamic sequence is developed, and the mapping relationship between basic expression and emotion is studied to construct the emotional model, …and the emotional state recognition of the learner is realized by the research on facial expression. In the intelligent teaching environment, the teacher adjusts the teaching strategy according to the emotional state recognition test results, improves the teaching efficiency, and realizes the wisdom teaching. Moreover, combined with the actual situation, an expression recognition algorithm based on the ultra-wide regression network model for unsupervised learning classroom education is constructed. Through experimental analysis, we can know that this research algorithm has certain advantages in facial expression recognition. Show more

Keywords: Ultra-wide regression network, unsupervised learning, classroom education, expression recognition, feature extraction

DOI: 10.3233/JIFS-179794

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