Journal of Intelligent & Fuzzy Systems - Volume 39, issue 6

Authors: Wang, Yile | Zeng, Dashuai

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. 39, no. 6, pp. 8867-8875, 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. 39, no. 6, pp. 8877-8886, 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. 39, no. 6, pp. 8887-8895, 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. 39, no. 6, pp. 8897-8905, 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. 39, no. 6, pp. 8907-8915, 2020

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

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. 39, no. 6, pp. 8917-8925, 2020

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

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. 39, no. 6, pp. 8927-8935, 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. 39, no. 6, pp. 8937-8942, 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. 39, no. 6, pp. 8943-8951, 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. 39, no. 6, pp. 8953-8960, 2020

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

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. 39, no. 6, pp. 8961-8969, 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. 39, no. 6, pp. 8971-8980, 2020

Authors: Liu, Xiaohua

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. 39, no. 6, pp. 8981-8988, 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. 39, no. 6, pp. 8989-8996, 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. 39, no. 6, pp. 8997-9005, 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. 39, no. 6, pp. 9007-9014, 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. 39, no. 6, pp. 9015-9026, 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. 39, no. 6, pp. 9027-9035, 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. 39, no. 6, pp. 9037-9044, 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. 39, no. 6, pp. 9045-9051, 2020

Authors: Wang, Wensheng | Yu, Han | 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. 39, no. 6, pp. 9053-9061, 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. 39, no. 6, pp. 9063-9071, 2020

Authors: Shan, Xianming | Liu, Huixin | Liu, Yefeng

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. 39, no. 6, pp. 9073-9083, 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. 39, no. 6, pp. 9085-9090, 2020