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

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