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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: He, Qian | Shao, Juwei | Pu, Jian | Zhou, Minjie | M, M. | Xiang, Shutian | Su, Wei
Article Type: Research Article
Abstract: Medical image recognition is affected by characteristics such as blur and noise, which cause medical image features that cannot be effectively identified and directly affects clinical diagnostics. In order to improve the diagnostic effect of medical MR image features, based on the FRFCM clustering segmentation method, this study combines the medical MR image feature reality, collects data for traditional clustering method analysis, and sorts out the shortcomings of traditional clustering methods. Simultaneously, this study improves the traditional clustering method by combining medical image feature diagnosis requirements. In addition, this study carried out image data processing through simulation, and designed comparative …experiments to analyze the performance of the algorithm. The research shows that the FRFCM combined with the intuitionistic fuzzy set proposed in this paper has greatly improved the noise immunity and segmentation performance compared with the FCM based fuzzy set. Show more
Keywords: FRFCM clustering, feature extraction, image segmentation, medical diagnosis
DOI: 10.3233/JIFS-189327
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2871-2879, 2021
Authors: Fu, Chao | Jiang, Hao | Chen, Xi
Article Type: Research Article
Abstract: Under the background of big data era, great changes have taken place in the education management of colleges and universities with the application of big data, and the trend of education management informatization is increasingly obvious. Therefore, in the wave of big data, the education management work will also undergo earth shaking changes. Colleges and universities should also keep up with the trend of the times, optimize and adjust the education management work, ensure that the student management work can meet the management needs of the era of big data, effectively improve various education management work, and provide better and …better services for students. Starting from the introduction of the connotation, characteristics and value of big data, based on the development status of university education management in the era of big data, this paper mainly analyzes the great significance of big data to the innovation of university education management and the challenges it faces, and finally analyzes the specific path of big data in university education management innovation. Show more
Keywords: Big data era, college education management, reform, innovative development
DOI: 10.3233/JIFS-189328
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2881-2890, 2021
Authors: Zhu, Wenqiang
Article Type: Research Article
Abstract: First, the recommendation system and its advantages are introduced in detail, and based on the characteristics of the intelligent topic logical interest set resource and user behavior in the existing intelligent topic logical interest set resource platform, a personalized fuzzy logic model of the intelligent topic logical interest set resource is established and adapted to it. The personalized fuzzy logic user personalized fuzzy logic interest model of personalized fuzzy logic is designed, and the user personalized fuzzy logic interest transfer method is designed to simulate the user learning process. Secondly, on the basis of the established model, according to the …idea of collaborative filtering, the personalized fuzzy logic user’s personalized fuzzy logic interest value and the user’s rating of resources are respectively predicted, and the two prediction results are combined to recommend resources to the user. Finally, the ontology is applied to user interest description, and a method based on personalized fuzzy logic user rough interest vector and nearest neighbor concept aggregation is proposed to find fine-grained user interest and recommend interest resources. Experimental tests show that this method can better describe the composition and development of user interests, making the recommendation effect of interest resources for specific users more accurate and reliable. The problem of collaborative recommendation in personalized fuzzy logic systems is further studied, the basic principles and typical technologies of collaborative recommendation are analyzed, and the collaborative recommendation method based on users with similar interests and the collaborative recommendation method based on weighted association rules are proposed. Show more
Keywords: Personalized fuzzy logic, interest model, recommendation of interest resources, collaborative recommendation
DOI: 10.3233/JIFS-189329
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2891-2901, 2021
Authors: Wang, Kun
Article Type: Research Article
Abstract: The optical fiber network has the characteristics of providing users with wider bandwidth and supporting the changing needs of more users. At the same time, the optical fiber network can also reduce the network infrastructure investment. The traditional Ad Hoc On-demand Distance Vector (AODV) algorithm does not consider the impact of node movement on the network, and the link disconnection frequently occurs during the routing process. The ant colony algorithm based on swarm intelligence only considers the unique factor of pheromone concentration to find the optimal path through multiple iterations, which will increase the complexity of the algorithm and affect …the route establishment delay. In response to the above problems, this paper proposes a routing algorithm based on fuzzy logic. The algorithm can comprehensively consider the three factors of node location, mobility and signal strength, and greatly reduces the complexity of the algorithm. This paper gives a detailed definition of profust reliability of the Ethernet Passive Optical Network (EPON) system for distribution network communication and obtains the profust reliability parameters based on Monte Carlo simulation. After that, the reliability of profust under different networking modes was simulated, and the influence of network scale, component failure rate, component repair time and other parameters on the reliability of EPON networking profust was analyzed. The fuzzy probist reliability analysis method uses analytical methods, which are commonly used to deal with end-to-end reliability analysis problems and has certain limitations. Profust reliability analysis treats the system as a whole, which is more suitable for the reliability of complex end-to-multi-end systems. Show more
Keywords: Fuzzy reliability, fuzzy logic, routing algorithm, optical fiber intelligent network access
DOI: 10.3233/JIFS-189330
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2903-2915, 2021
Authors: He, Lina | He, Laibin
Article Type: Research Article
Abstract: With the rapid development of science and technology, positioning technology has been widely used in people’s daily lives and related scientific research activities. However, the traditional positioning system mostly uses GPS for positioning, and then transmits the positioning information to the remote server through GPRS / GSM, but it is not applicable in remote mountain areas where some base station signals cannot reach. Moreover, the accuracy of single GPS positioning is difficult to be guaranteed. This paper mainly studies the design of Beidou-GPS dual-mode positioning system based on Android platform mobile communication equipment. First, analyse the composition of the satellite …positioning system and design the overall architecture of the Beidou-GPS dual-mode positioning system for mobile communication equipment. Then, it analyses the most important star selection algorithm in dual-mode positioning technology, and proposes an improved star selection algorithm based on azimuth. Second, build the overall architecture of the Android platform for mobile communication devices based on dual-mode positioning. Finally, by comparing with the traditional star selection algorithm, the proposed improved positioning algorithm is experimentally verified. Simulation experiment results show that the proposed dual-mode positioning algorithm has high accuracy and can meet the real-time requirements of the system. Show more
Keywords: Beidou-GPS dual mode, star selection algorithm, Android platform, mobile communication equipment
DOI: 10.3233/JIFS-189331
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2917-2928, 2021
Authors: Sun, Pingping | Gu, Lingang
Article Type: Research Article
Abstract: Fuzzy knowledge graph system is a semantic network that reveals the relationships between entities, and a tool or methodology that can formally describe things in the real world and their relationships. Smart education is an educational concept or model that uses advanced information technology to build a smart environment, integrates theory and practice to build an educational framework for information age, and provides paths to practice it. Artificial intelligence (AI) is a comprehensive discipline developed by the interpenetration of computer science, cybernetics, information theory, linguistics, neurophysiology and other disciplines, which is a direction for the development of information technology in …the future. On the basis of summarizing and analyzing of previous research works, this paper expounded the research status and significance of AI technology, elaborated the development background, current status and future challenges of the construction and application of fuzzy knowledge graph system for smart education, introduced the methods and principles of data acquisition methods and digitalized apprenticeship, realized the process design, information extraction, entity recognition and relationship mining of smart education, constructed a systematic framework for fuzzy knowledge graph, and analyzed the high-quality resources sharing and personalized service of AI-assisted smart education, discussed automatic knowledge acquisition and fusion of fuzzy knowledge graph, performed co-occurrence relationship analysis, and finally conducted application case analysis. The results show that the smart education knowledge graph for AI-assisted smart education can integrate teaching experience and domain knowledge of discipline experts, enhance explainable and robust machine intelligence for AI-assisted smart education, and provide data-driven and knowledge-driven information processing methods; it can also discover the analysis hotspots and main content of research objects through clustering of high-frequency topic words, reveal the corresponding research structure in depth, and then systematically explore its research dimensions, subject background and theoretical basis. Show more
Keywords: AI-assisted smart education, fuzzy knowledge graph, AI technology, system construction
DOI: 10.3233/JIFS-189332
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2929-2940, 2021
Authors: Luo, Gang | Chen, Zhiyuan
Article Type: Research Article
Abstract: In this paper, through the edge computing application path, the educational evaluation system was optimized using the adaptive entropy theory polymerization method which based on applying the path. By adding multiple constraints to filter out nodes and educational evaluation edges that do not meet the requirements, the improved algorithm is used to optimize the redundant paths to avoid loops and node detour problem. To improve the accuracy of education evaluation and evaluation, ensure the load balance in the domain, and solve the problems of single evaluation attribute and high overlap of education evaluation paths. This paper proposes a multi-attribute education …evaluation model that refines the evaluation attributes of education evaluation and uses analytic hierarchy process perform weight distribution. The algorithm can improve the accuracy of the evaluation of the education evaluation system while ensuring the computational efficiency, and can ensure the load balance within the domain, and improve the network survival time. Show more
Keywords: Edge computing, education evaluation system, application path, optimization research
DOI: 10.3233/JIFS-189333
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2941-2951, 2021
Authors: Wang, Li
Article Type: Research Article
Abstract: This paper discusses the modeling of financial volatility under the condition of non-normal distribution. In order to solve the problem that the traditional central moment cannot estimate the thick-tailed distribution, the L-moment which is widely used in the hydrological field is introduced, and the autoregressive conditional moment model is used for static and dynamic fitting based on the generalized Pareto distribution. In order to solve the dimension disaster of multidimensional conditional skewness and kurtosis modeling, the multidimensional skewness and kurtosis model based on distribution is established, and the high-order moment model is deduced. Finally, the problems existing in the traditional …investment portfolio are discussed, and on this basis, the high-order moment portfolio is further studied. The results show that the key lies in the selection of the model and the assumption of asset probability distribution. Financial risk analysis can be effective only with a large sample. High-frequency data contain more information and can provide rich data resources. The conditional generalized extreme value distribution can well describe the time-varying characteristics of scale parameters and shape parameters and capture the conditional heteroscedasticity in the high-frequency extreme value time series. Better describe the persistence and aggregation of the extreme value of high frequency data as well as the peak and thick tail characteristics of its distribution. Show more
Keywords: Dynamic financial economic fluctuation, non-normal distribution, mathematical model
DOI: 10.3233/JIFS-189334
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2953-2962, 2021
Authors: Zhuang, Zaixing | Zhong, lijie | Zhu, Xianwu | Miao, Miao | Wu, Cheng | Miao, Jianxia
Article Type: Research Article
Abstract: The current application of intelligent algorithms has achieved certain applications in smart medical, but its application in the automatic grading of admitted patients is in a blank, which makes it difficult to allocate hospital resources effectively. In order to improve the efficiency and accuracy of automatic classification of patients admitted to hospital, this study builds the corresponding genetic algorithm operator based on genetic algorithm. At the same time, this paper uses the random method to generate the initial population and uses the inversion mutation operator to perform the mutation operation. In addition, this article combines image processing to automatically classify …patient types and patient levels. Finally, this paper uses the data collection method to verify the model and input the data into the research model. The research shows that the model proposed in this paper has certain effects, which can realize the automatic grading of patients admitted, and can provide theoretical reference for subsequent related research. Show more
Keywords: Genetic algorithm, admission, patient grading, intelligent grading
DOI: 10.3233/JIFS-189335
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2963-2972, 2021
Authors: Tang, Shuangxia | Shi, Kunquan
Article Type: Research Article
Abstract: Wearable-devices have developed rapidly. Meanwhile, the security and privacy protection of user data has also occurred frequently. Aiming at the process of privacy protection of wearable-device data release, based on the conventional V-MDAV algorithm, this paper proposes a WSV-MDAV micro accumulation method based on weight W and susceptible attribute value sensitivity parameter S and introduces differential-privacy after micro accumulation operating. By simulating the Starlog dataset and the Adult dataset, the results show that, compared with the conventional multi-variable variable-length algorithm, the privacy protection method proposed in this paper has improved the privacy protection level of related devices, and the information …distortion has been properly resolved. The construction of the release model can prevent susceptible data with identity tags from being tampered with, stolen, and leaked by criminals. It can avoid causing great spiritual and property losses to individuals, and avoid harming public safety caused by information leakage. Show more
Keywords: Wearable-device, data privacy-protection, micro accumulation, differential privacy
DOI: 10.3233/JIFS-189336
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2973-2980, 2021
Authors: Mao, Jian | Liu, Jinming | Zhang, Jiemin | Han, Zhenzhong | Shi, Sen
Article Type: Research Article
Abstract: The unintentional electromagnetic (EM) emission of computer monitors may cause the leakage of image information displayed on the monitor. Detection of EM information leakage risk is significant for the information security of the monitor. The traditional detection method is to verify EM information leakage by reconstructing an image from EM emission. The detection method based on image reconstruction has limitations: adequate signal sampling rate, accurate synchronization signal, and dependence on operational experience. In this paper, we analyze the principle of image information leakage and propose an innovative detection method based on Convolutional Neural Network (CNN). This method can identify the …image information in EM emission to verify the EM information leakage risk of the monitor. It overcomes the limitations of the traditional method with machine learning. This is a new attempt in the field of EM information leakage detection. Experimental results show that it is more adaptable and reliable in complex detection environment. Show more
Keywords: Convolutional neural network, electromagnetic information leakage, image identification, information security, computer monitor
DOI: 10.3233/JIFS-189337
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2981-2991, 2021
Authors: He, Gongfei | Zhang, Bingyi | Feng, Guihong
Article Type: Research Article
Abstract: With the wide application of electric drive equipment and variable frequency load, the power supply system based on the DC grid has attracted much attention because of its high energy density and simple control, and the operation mode of rectifier AC synchronous generators operating in parallel is often adopted. The available topology structures of the rectifier permanent magnet (PM) generator sets are analyzed in this paper, the parallel operation principle of uncontrolled rectifier PM generator sets is analyzed in theory. The parallel operation characteristics of the generator sets are summarized when the voltage-stabilizing and power balanced measures are not taken, …and the influence factors of power balancing among parallel operation generators are analyzed. The power-balanced method of rectifier generator sets operating in parallel based on a master-slave control strategy is proposed, which can realize power balanced with the closed-loop control of the DC side output current. The simulation and experiment results show that the proposed method can realize the power balanced control of rectifier generator sets operating in parallel well. The output power of each generator set can be distributed according to capacity. The rationalization proposal of how to matching generators’ parameters in the power supply system of rectifier PM generator sets operating in parallel is given. Show more
Keywords: PM generator, uncontrolled rectifier, operating in parallel, power balanced control, mobile power supply
DOI: 10.3233/JIFS-189338
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2993-3003, 2021
Authors: Li, Xiaowen | Li, Jianwei | Liu, Cheng | Chen, Chuanbin
Article Type: Research Article
Abstract: The tailings dam safety monitoring system is a system that plays an important role in disaster prevention and reduction. This paper divides the whole network of mine dam safety monitoring systems into two parts, that is, the basic wireless network and GPRS network from the gateway to the monitoring center. First, it’s the hardware of the design module, the network is divided into uplink communication and downlink communication, uplink communication is to upload the dam data collected by the terminal node to the gateway through the network. Downlink communication is the instruction sent by the gateway to the monitoring center, …send to terminal nodes through data conversion between protocols. Secondly, the gateway also needs to solve the data conversion between the network and GPRS network protocol, so that the entire security monitoring system can communicate accurately. The communication between gateway and monitoring center is realized through the GPRS network, this requires adding the GPRS communication module to the gateway module. To increase the diversity of communications, communication between GSM short message communication methods and monitoring centers has also increased. The experimental results prove that the system in this paper can be applied to the mine dam safety monitoring system, meet the design requirements. Show more
Keywords: Internet of things, safety monitoring, wireless sensor networks, tailing dam
DOI: 10.3233/JIFS-189339
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3005-3014, 2021
Authors: Guan, Shuai
Article Type: Research Article
Abstract: With the continuous implementation of the Belt and Road Initiative of China, cross-border e-commerce is gradually becoming one of the main ways of trade. The smart operation of cross-border logistics has become an important factor affecting the quality of cross-border e-commerce transactions by its characteristics of high-efficiency, high-quality, and low-cost. As China’s first smart city in China with the theme of the aviation economy, the top priority for developing cross-border e-commerce in the Zhengzhou Airport Economic Zone is to construct cross-border e-commerce smart logistics. This paper expounds on the significance of applying big data technology on the construction of the …intelligent logistics, analyzing its important roles not only in further promoting the cross-border e-commerce development in the Zhengzhou Airport Economy Zone but also during the process of the entire national economic transformation and escalation. The smart logistics constructing strategy in the Zhengzhou Airport Economy Zone is expected to provide ideas and support for the Zhengzhou Airport Economy Zone making continuous improvement in leading and pushing the Henan regional economy to achieve sustainable development in the future. Show more
Keywords: Smart logistics construction, big data, cross-border e-commerce, the Zhengzhou airport economy zone
DOI: 10.3233/JIFS-189340
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3015-3023, 2021
Authors: Zheng, Haoxin | Huang, Minghui | Zhan, Lihua | Liu, Peiyao | Zhu, Ziqing
Article Type: Research Article
Abstract: The actuator is an important component of missiles and other aircraft to maintain the flight attitude. A method to calculate the power of the electric servo motor was proposed according to the load characteristics’ of both the servo motor and actuator. An optimization method for the transmission reduction ratio was obtained by considering the load torque equation. Dynamics simulations of the actuator were conducted under a variety of conditions. The simulation results show that the clearance and the friction between the ball screw and the fork, which consist of the transmission mechanism, induce the torque fluctuations, as a source of …noise in the motor load. According to the optimization design of the Electric, the Actuator prototype has passed the test, the performance meets the design requirements. Show more
Keywords: Actuator, dynamic simulation, load characteristics, friction, clearance
DOI: 10.3233/JIFS-189341
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3015-3023, 2021
Authors: Zhou, Jianheng | Xu, Rongfei
Article Type: Research Article
Abstract: In product sales with network externalities, a Stackelberg game model is established with a new product and an existing product in the market, investigating the influence of first-mover strategy and non-strategic pricing model on the pricing, market share, and profit of an enterprise. Furthermore, the influence of network externalities and transfer costs on the strategies of latecomers is studied. Finally, the market equilibrium is analyzed. The results show that under the strategic pricing, the first entrant grabs the market share with low price and low profit in the first stage, to obtain greater network externalities in the second stage, enhance …the competitiveness with latecomer, and make the total revenue greater. Given network externalities and transfer costs, the strategic behavior of the first entrant makes it harder for the later entrant to enter the market. Show more
Keywords: Network externalities, long-term pricing, transfer costs, strategic pricing, equilibrium analysis
DOI: 10.3233/JIFS-189342
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3035-3043, 2021
Authors: Zhou, Chengmin | Huang, Ting | Liang, Shuang
Article Type: Research Article
Abstract: Smart home products and equipment are relatively expensive while using specific physical objects to prove functional characteristics, the cost is high, and it is difficult to meet the personal needs of customers. Based on the above background, the purpose of this research is the application and design of a smart home R&D system based on virtual reality. This study proposes the concept of introducing virtual reality methods into the control scene given the shortcomings of the existing smart home control interface interaction methods. From the perspective of being more suitable for the user’s needs, the virtual reality method is used …to optimize the smart home interaction methods. Through the analysis of the user’s lifestyle and needs, the functional module model of applying virtual reality to the smart home control scheme is established. Then, by collecting data, use Sketchup software to build and optimize the model of the simulation system to build a realistic family scene model. Finally, through the integrated use of the Unity 3D rendering engine and the virtual simulation system technology, the intelligent simulation of the interior functions of the house is realized. Experimental results show that using virtual reality to optimize the interaction of smart homes, the control method is relatively simple, and the cost can be reduced by about 20%. Show more
Keywords: Smart home, virtual reality, 3d modeling, natural interaction
DOI: 10.3233/JIFS-189343
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3045-3054, 2021
Authors: Wang, Gang | Zhou, Jun
Article Type: Research Article
Abstract: With the development of science and technology, the intelligent robot has become an important tool in our production and life. It not only improves people’s living standards but also promotes economic development. At present, the related technology in the field of the intelligent robot has been developed rapidly, but at the same time, many technical problems have been exposed. The single path planning problem can be well solved, but the dynamic path planning of a robot is one of the current technical difficulties. At present, the genetic algorithm is the mainstream scheme, but its control accuracy is still lacking in …practical application. To solve this problem, this paper proposes a dynamic path planning scheme for intelligent robots based on a fuzzy neural network. The research of this paper is mainly divided into four parts. The first part is to analyze the current situation of technology research in this field and put forward the idea of this paper by analyzing the shortcomings of existing technologies. The second part is the research of related basic theory, which deeply studies the core theory of intelligent robot and dynamic path planning, which provides a theoretical basis for the later model implementation. The third part is the design and implementation of dynamic path planning based on a fuzzy neural network. This paper gives the design principle and specific improvement method in detail. At the end of the paper, that is, the fourth part, through comparative analysis experiments, further proves the superiority of the fuzzy neural network algorithm. Compared with the traditional particle swarm optimization algorithm, it can significantly improve the control accuracy and robustness of the model. Show more
Keywords: Neural networks, fuzzy theory, intelligent systems, intelligent robot
DOI: 10.3233/JIFS-189344
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3055-3063, 2021
Authors: Ren, Yanhong | Chen, Bo | Li, Aizeng
Article Type: Research Article
Abstract: Action is the key to sports and the core factor of standardization, quantification, and comprehensive evaluation. However, in the actual competition training, the occurrence of sports activities is often fleeting, and it is difficult for human eyes to identify quickly and accurately. There are many existing quantitative analysis methods of sports movements, but because there are many complex factors in the actual scene, the effect is not ideal. How to improve the accuracy of the model is the key to current research, but also the core problem to be solved. To solve this problem, this paper puts forward an intelligent …system of sports movement quantitative analysis based on deep learning method. The method in this paper is firstly to construct the fuzzy theory human body feature method, through which the influencing factors in the quantitative analysis of movement can be distinguished, and the effective classification can be carried out to eliminate irrelevantly and simplify the core elements. Through the method of human body characteristics based on fuzzy theory, an intelligent system of deep learning quantitative analysis is established, which optimizes the algorithm and combines many modern technologies including DBN architecture. Finally, the accuracy of the method is improved by sports action detection, figure contour extraction, DBN architecture setting, and normalized sports action recognition and quantification. To verify the effect of this model, this paper established a performance comparison experiment based on the traditional method and this method. The experimental results show that compared with the traditional three methods, the accuracy of the in-depth learning sports movement quantitative analysis method in this paper has greatly improved and its performance is better. Show more
Keywords: Action recognition, sports movement, deep learning, action characteristics
DOI: 10.3233/JIFS-189345
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3065-3073, 2021
Authors: Zhao, Kai | Jiang, Wei | Jin, Xinlong | Xiao, Xuming
Article Type: Research Article
Abstract: The traditional sports match analysis mostly adopts the method of manual observation and recording, which is not only time-consuming and laborious but also has the defects of subjectivity and inaccuracy in the judgment results, resulting in the deviation of the match data analysis and statistical results. The purpose of this paper is to study an artificial intelligence system that can automatically analyze and evaluate the effect of both sides in volleyball matches. In this paper, the system is divided into two steps: detection and tracking of moving objects, recognition, and classification of players’ behaviors and movements. About moving target detection …and tracking, this paper proposes a moving target fast detection framework based on a mixture of mainstream technologies and a MeanShift target tracking method based on Kalman filtering and adaptive target region size. For behavior and action recognition and classification, this paper proposes a classifier combining BP neural network and support vector machine. Experimental results show that the proposed algorithm and classifier are effective. By analyzing the performance of the proposed classifier, the classification accuracy is 98%. Show more
Keywords: Intelligent analysis, volleyball match, artificial intelligence, target recognition algorithm, behavior classification algorithm
DOI: 10.3233/JIFS-189346
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3075-3084, 2021
Authors: Xu, Wenhan | Bo, Hongguang | Chen, Yinglian
Article Type: Research Article
Abstract: In order to explore the impact of the system-driven supply chain, collaborative operations, and organizational characteristics on supply chain operational performance, this paper based on the system dynamics method to simulate the established information collaborative supply chain model, analyze market demand data, inventory before and after the supply chain sharing The changes of inventory fluctuations in the supply chain and related calculations are compared with the simulation results under the current model to prove the importance of implementing information collaboration in the supply chain of a large retailer-led supply chain. The research in this paper shows that with the supply …chain information collaboration model, the average value of the manufacturer’s order quantity has dropped by 30.4%. Affected by this, the dispersion coefficient has also dropped from 0.76 to 0.6, and the average number of orders in the distribution center has also dropped by 12.2%; With the supply chain information synergy model, the average value of the raw material inventory of manufacturers has dropped significantly, from 3400 in the current model to 2500 in the information synergy model, a decrease of 27%, the standard deviation has also decreased by 57%, and the dispersion coefficient has dropped from 0.98 to 0.50; The standard deviation rate of the inventory of the distribution center is 30%; from the perspective of the overall retail supply chain, the inventory has fallen by 14%, the standard deviation has fallen by 34%, and the dispersion coefficient has dropped from 0.76 in the current model to the information collaboration model. 0.6, it can be seen that the mode of supply chain information coordination has a great effect on reducing supply chain costs and improving supply chain efficiency. Show more
Keywords: System dynamics, supply chain management, information collaboration, a supply chain operating performance
DOI: 10.3233/JIFS-189347
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3085-3095, 2021
Authors: Zhao, Jinghua | Lin, Jie | Liang, Shuang | Wang, Mengjiao
Article Type: Research Article
Abstract: The paper first analyzes the correlation between text sentiment values and personality traits, proves that text sentiment can have a good support effect on user personality prediction, then on this basis, a method based on CNN-LSTM is proposed, which can be used to deeply analyze the sentiment analysis capability of the model, hoping to improve the precision of sentiment classification and lay a solid foundation for the next experiment. This experiment proves that the CNN-LSTM constructed in this paper can better predict the emotional tendency of the short text of microblog, has good generalization ability, and has higher precision than …other methods. Show more
Keywords: CNN-LSTM, sentiment annotation, social media, personality
DOI: 10.3233/JIFS-189348
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3097-3106, 2021
Authors: Fu, Qiang | Ma, Li | Li, Chao | Li, Zhi | Zhu, Zhengyu | Lin, Zhiran
Article Type: Research Article
Abstract: At present, the majority of sports games video adopts MPEG image technology, and MPEG video compression is the current more mainstream approach. After compression, the quality of the video will decline, and other practical problems. However, the existing detection methods of sports video scene conversion, when dealing with MPEG compressed video, are not ideal, often appear the phenomenon of missing detection and wrong detection. In order to solve this problem, this paper proposes a detection method of sports scene conversion on MPEG compressed video based on fuzzy logic. Introducing fuzzy logic into the detection method of video scene conversion is …the highlight of this method. Firstly, this paper preprocessed the video image according to the Convention. In this paper, the recognition of image features and specific extraction methods are introduced in detail, and the extraction algorithm of image color features is further optimized. For the design of the detection method, the main innovation is to fully combine the fuzzy logic and macroblock information. In the existing detection methods, different detection schemes are given for the abrupt change of video scene and the gradual change of scene. Finally, in order to verify the actual effect of the detection method in this paper, an experimental analysis based on the keyframe complexity detection method is established. After a number of experiments including the experimental results of scene transition, analysis, and processing time, through the analysis of data, a step-by-step proof of this method has good accuracy and recall. Show more
Keywords: Fuzzy logic, MPEG compression technology, scene detection; sports video
DOI: 10.3233/JIFS-189349
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3107-3115, 2021
Authors: Li, Zhipeng | Li, Xiaolan | Shi, Ming | Song, Wenli | Zhao, Guowei | Yang, Ruizhu | Li, Shangbin
Article Type: Research Article
Abstract: Snowboarding is a kind of sport that takes snowboarding as a tool, swivels and glides rapidly on the specified slope line, and completes all kinds of difficult actions in the air. Because the sport is in the state of high-speed movement, it is difficult to direct guidance during the sport, which is not conducive to athletes to find problems and correct them, so it is necessary to track the target track of snowboarding. The target tracking algorithm is the main solution to this task, but there are many problems in the existing target tracking algorithm that have not been solved, …especially the target tracking accuracy in complex scenes is insufficient. Therefore, based on the advantages of the mean shift algorithm and Kalman algorithm, this paper proposes a better tracking algorithm for snowboard moving targets. In the method designed in this paper, in order to solve the problem, a multi-algorithm fusion target tracking algorithm is proposed. Firstly, the SIFT feature algorithm is used for rough matching to determine the fuzzy position of the target. Then, the good performance of the mean shift algorithm is used to further match the target position and determine the exact position of the target. Finally, the Kalman filtering algorithm is used to further improve the target tracking algorithm to solve the template trajectory prediction under occlusion and achieve the target trajectory tracking algorithm design of snowboarding. Show more
Keywords: Snowboarding, multi-target matching tracking, occluding target, multi-algorithm fusion
DOI: 10.3233/JIFS-189350
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3117-3125, 2021
Authors: Lu, Yan’an | Shi, Lei
Article Type: Research Article
Abstract: This research mainly discusses the characteristics of BIM architecture design and its application in traditional residential design from the perspective of smart cities. Given the topics that people are more concerned about, this research mainly uses BIM modeling technology to initially build a virtualized building model. It discusses the convenience of intelligent automation technology in terms of resource consumption and house security. In terms of safety, different levels of wind blowing strength are mainly used to measure the distance moved by the house to evaluate the safety factor. Divide the wind blowing intensity into A, B, C, D, E, F, …and 6 levels to test the strength of the house. When the wind intensity level is F, the safety factor is the weakest, which is 20%. When conducting a house consumption test, directly measure the house’s electricity consumption within a specified time to conduct a resource rate consumption test. Divide the time period into 1 h, 2 h, 3 h, 4 h, 5 h, 6 h, 6 different time periods to measure power consumption. The resource consumption rate reaches a maximum value of 96% when the length of time is 6 h. The experimental results show that the safety characteristics of BIM technology are the weakest when the wind strength level is F, and the safety performance is different when the wind strength level is different. In terms of resource consumption, the resource consumption rate reaches the maximum value when the time is 6 h, and the length of time directly determines the housing resource consumption rate. From the perspective of a smart city, BIM building design has the advantages of low resource consumption and high safety factor. Show more
Keywords: Smart city, BIM architectural design, traditional residential design, safety factor, house strength
DOI: 10.3233/JIFS-189351
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3127-3136, 2021
Authors: Zhao, Chen | Xue, Ye | Niu, Tong
Article Type: Research Article
Abstract: Nowadays, with the development of science and technology, the progress of society, and the fierce competition among enterprises in the market, the current market competition has gradually turned into the competition of talents, and the excellent talent reserve of enterprises is a competitive advantage. However, there are many enterprises and many places where human resource management is not in place. At the same time, many imperceptible problems in human resource management, most of which are hidden and uncertain, lead to business problems and related phenomena and threaten the further development of enterprises. Although there are many research methods for these …problems, it is difficult to analyze the current situation with this method because of its strong subjectivity. In order to better solve the above problems, this paper studies the standard system of human resource management under the background of the fuzzy system and uses the new structure of human resource fuzzy theory decision-making which has strong theoretical and practical value in human resource system. In the research of this paper, human resource management indicators are divided into comprehensive and professional. Aiming at these two categories of indicators, this paper uses human resource management theory to analyze them systematically and designs a more reasonable indicator system. Then, taking an enterprise as an example, it uses a fuzzy comprehensive evaluation method to combine qualitative and quantitative research to analyze the enterprise. In the analysis, this paper finds that there are some problems in human resource management, such as performance management is not in place, employees’ sense of belonging is not strong, and through the fuzzy comprehensive evaluation of the enterprise situation, it is found that the enterprise human resource management system is good, but still needs to further improve the enterprise management system. Show more
Keywords: Fuzzy theory, human resource management theory, comprehensive evaluation
DOI: 10.3233/JIFS-189352
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3137-3146, 2021
Authors: Zheng, Xiangyu | Jia, Rong | Aisikaer, | Gong, Linling | Zhang, Guangru | Dang, Jian
Article Type: Research Article
Abstract: Ensuring the stable and safe operation of the power system is an important work of the national power grid companies. The power grid company has established a special power inspection department to troubleshoot transmission line components and replace faulty components in a timely manner. At present, assisted manual inspection by drone inspection has become a trend of power line inspection. Automatically identifying component failures from images of UAV aerial transmission lines is a cutting-edge cross-cutting issue. Based on the above problems, the purpose of this article is to study the component identification and defect detection of transmission lines based on …deep learning. This paper expands the dataset by adjusting the size of the convolution kernel of the CNN model and the rotation transformation of the image. The experimental results show that both methods can effectively improve the effectiveness and reliability of component identification and defect detection in transmission line inspection. The recognition and classification experiments were performed using the images collected by the drone. The experimental results show that the effectiveness and reliability of the deep learning method in the identification and defect detection of high-voltage transmission line components are very high. Faster R-CNN performs component identification and defect detection. The detection can reach a recognition speed of nearly 0.17 s per sheet, the recognition rate of the pressure-equalizing ring can reach 96.8%, and the mAP can reach 93.72%. Show more
Keywords: Power line detection, deep learning, component recognition, faster R-CNN, network model
DOI: 10.3233/JIFS-189353
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3147-3158, 2021
Authors: Li, Weiguang
Article Type: Research Article
Abstract: With the vigorous promotion of the construction of smart campus by the ministry of education, the development concept of smart campus will have broad application prospects. However, colleges and universities are still at the stage of digital campus and there are many problems left. It is difficult to complete the transition from digital campus to smart campus. The main problem is that the campus data has only been digitized but not informational. The purpose of this article is to study a smart campus management system based on the Internet of Things technology. This research uses the unified data collection source …of face recognition terminal hardware products based on the Internet of Things technology, unified management in the background of the system, and calculates and analyzes the data to obtain valuable campus big data. This study designed and implemented a complete smart campus management system by analyzing the system design principles and design goals. This system is mainly divided into the face recognition terminal hardware and smart campus software system based on the Internet of Things. By analyzing the data generated by students and faculty and staff, it can provide a reference for campus managers to improve management quality, and help teachers and students to formulate more efficient learning and teaching and research plans. This article tests the practicability of the system and obtains the user’s satisfaction as 8.0. Show more
Keywords: Internet of things, smart campus, management system, big data, smart terminal
DOI: 10.3233/JIFS-189354
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3159-3168, 2021
Authors: Liu, Ying | Wang, Guoshi | Guo, Wei | Zhang, Yingbin | Dong, Weiwei | Guo, Wei | Wang, Yan | Zeng, ZhiXiang
Article Type: Research Article
Abstract: The power grid is the foundation of the development of the national industry. The rational and efficient distribution of power resources plays an important role in economic development. The smart grid is the use of modern network information technology to realize the exchange of data information between grid devices. The construction of smart grids has accumulated a huge amount of data resources. At present, the demand for power companies to “use data management enterprises and use the information to drive services” is increasingly urgent. Power big data has become the basis for grid companies to make decisions, but the accumulation …of pure data does not bring benefits to grid companies. Therefore, making full use of these actual data based on the grid, in-depth analysis, and discovering and using the hidden information is of great significance for guiding the power companies to make correct decisions. This paper first analyzes the differences between smart grids and traditional grids and provides an overview of data mining techniques, including the association rules commonly used in association analysis. Then the application scenarios of data mining in the smart grid are put forward, and data mining technology is applied to power load forecasting. The experimental results show that the data mining method and actual results of the power load forecasting in the smart grid environment proposed in this paper are within a reasonable range. Therefore, the results of load forecasting in this paper are still of practical value. Show more
Keywords: Smart grid, data mining, big data, association rules
DOI: 10.3233/JIFS-189355
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3169-3175, 2021
Authors: Xindi, Yang | Huanran, Du
Article Type: Research Article
Abstract: The intelligent scheduling algorithm for hierarchical data migration is a key issue in data management. Mass media content platforms and the discovery of content object usage patterns is the basic schedule of data migration. We add QPop, the dimensionality reduction result of media content usage logs, as content objects for discovering usage patterns. On this basis, a clustering algorithm QPop is proposed to increase the time segmentation, thereby improving the mining performance. We hired the standard C-means algorithm as the clustering core and used segmentation to conduct an experimental mining process to collect the ted QPop increments in practical applications. …The results show that the improved algorithm has good robustness in cluster cohesion and other indicators, slightly better than the basic model. Show more
Keywords: Data migration, media content, QPop, log mining
DOI: 10.3233/JIFS-189356
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3177-3184, 2021
Authors: Lu, Chen | He, Beina | Zhang, Rui
Article Type: Research Article
Abstract: Aiming at the problem of low accuracy of the current English interpretation teaching quality evaluation, a teaching quality evaluation method based on a genetic algorithm (GA) optimized RBF neural network is proposed. First, the principal component analysis is used to select the teaching quality evaluation index, and then design The RBF neural network teaching evaluation model is used, and GA is used to optimize the initial weights of the RBF neural network. Experimental results show that this method can effectively evaluate the quality of English interpretation teaching, and has high accuracy and real-time performance.
Keywords: English interpretation teaching, quality evaluation, RBF neural network, genetic algorithm, principal component analysis
DOI: 10.3233/JIFS-189357
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3185-3192, 2021
Authors: Zhang, Xia | Tao, Sihan | Hu, Jinjia | Lin, Shuai | Hashimoto, Minoru
Article Type: Research Article
Abstract: Wearable robots must adjust the assist mode/intensity according to human motion during the motion assistance process. By decoding the surface electromyography (sEMG) signal, the standard deviation of the fractal dimension is used as a characteristic index of muscle contraction-relaxation ability, and explore the feasibility of using the standard deviation of the fractal dimension to estimate the human motor function and thus provide a basis for decision-making for the flexible control of wearable robots. First, the sEMG signals of several subjects with different motor functions were collected and their time-domain and frequency-domain features were extracted. The experimental results for one hour …of walking showed that the time-domain and frequency-domain feature values increased with muscle fatigue. The trend has little to do with the inherent motor function of the human body; Second, due to the strong nonlinearity, time-varying, and strong complexity of the sEMG signal, the fractal dimension nonlinear method is used to characterize the complexity of the EMG signal that is closely related to muscle function. Besides, theoretical and experimental studies have been conducted to clarify the feasibility of the complexity of fractal dimension representation and to provide theoretical support for the further use of the standard deviation of fractal dimension to estimate human motor function. The experimental results of continuous walking for one hour show that, macroscopically, the fractal dimension of each muscle of the individual subject does not change significantly with walking time, which shows that the fractal dimension has nothing to do with exercise time and muscle fatigue; On the microscopic level, the value of the fractal dimension changes when the subject’s muscles contract and relax. Subjects with strong motor function have smaller fractal dimensions when their muscles contract than subjects with weaker motor function, and the opposite happens when their muscles relax, and it can be seen that there is a positive correlation between the difference in the fractal dimension during muscle contraction and relaxation and the muscle contraction-relaxation ability and the human body’s inherent motor function. The test results verify the feasibility of using the standard deviation of fractal dimension to estimate the intrinsic motor function of the human body. Show more
Keywords: EMG signal, human-robot interaction, standard deviation of fractal dimension, human motor function
DOI: 10.3233/JIFS-189358
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3193-3205, 2021
Authors: Xiaoman, Liu
Article Type: Research Article
Abstract: This article has been retracted, and the online PDF has been watermarked “RETRACTED”. A retraction notice is available at https://doi.org/10.3233/JIFS-219219 .
DOI: 10.3233/JIFS-189360
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3207-3214, 2021
Authors: Yang, XinShun | Zhou, JiaJia | Wen, DaoQun
Article Type: Research Article
Abstract: To improve the effectiveness and intelligence of university teaching management evaluation, the particle swarm optimization BP neural network algorithm is applied to the analysis of university teaching management evaluation data. BP neural network is used to model the evaluation index of teaching management, and then particle swarm optimization is used to optimize the weight and threshold of the neural network transfer function to ensure that the output of the BP neural network can obtain the global optimal solution. The experimental results show that the proposed algorithm has a good fit between the predicted value and the actual value of the …evaluation object of teaching management in Colleges and universities, and has a strong promotion value. Show more
Keywords: Teaching management evaluation, particle swarm optimization, BP neural network, normal distribution, weight, threshold value
DOI: 10.3233/JIFS-189361
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3215-3221, 2021
Authors: Zhang, Lingxue | Wu, Haitao
Article Type: Research Article
Abstract: Taking the rapid development of electronic science and technology as an opportunity, MCU which undertakes the equipment control task is developing towards the direction of intelligence, self-learning and multi-function integration. They have been applied to all aspects of human production and life. Driven by computer network technology, the development of Internet of Things technology is promoted. In this era, only by strengthening the research and development and improvement of MCU control system can we promote the development of the entire society and economy. This article mainly studies the application of MCU Technology in IoT electronics. This article first briefly explains …the definition of MCU, and then summarizes the entire development process of MCU. On this basis, it is effectively combined with the actual situation, and puts forward the practical application of the MCU Technology in the Internet of Things electronic products. On the basis of ensuring that the personalized needs of modern people are met, it can lay a good foundation for the future development of electronic products. The research experiments in this paper found that up to 70 meters, and found that a large number of packet loss has affected the basic communication. It is believed that communication can be performed at 70 meters but the communication quality is poor. It is not recommended to use, and the test is terminated. It can be seen from the results that the communication distance of the terminal node is finally within 30 meters, which can ensure that the data is almost 100% received. The packet loss rate within 60 meters is within 2%, and the communication quality is good. Guarantee basic communication functions. Show more
Keywords: Internet of things, electronic products, single chip technology, technology research, sensor technology
DOI: 10.3233/JIFS-189362
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3223-3233, 2021
Article Type: Other
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3235-3235, 2021
Authors: Saravanan, Vijayalakshmi
Article Type: Editorial
DOI: 10.3233/JIFS-189363
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3237-3238, 2021
Authors: Hailong, Liang
Article Type: Research Article
Abstract: The problems and disadvantages of the traditional teaching mode of Taekwondo in colleges and universities are obvious, which is not conducive to cultivating the interest of contemporary college students in learning Taekwondo. In order to improve the teaching effect of Taekwondo, based on the intelligent algorithm of human body feature recognition, this study uses support vector machine to construct a Taekwondo teaching effect evaluation model based on artificial intelligence algorithm. The model corrects the movement of the students by recognizing the movement characteristics of the students’ Taekwondo and can conduct the movement guidance and exercises through the simulation method. In …order to verify the performance of the model in this study, this study set up control experiments and mathematical statistical methods to verify the performance of the model. The research results show that the model proposed in this paper has a certain effect and can be applied to teaching practice Show more
Keywords: Artificial intelligence, improved algorithm, Taekwondo, teaching effect, evaluation and analysis
DOI: 10.3233/JIFS-189364
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3239-3250, 2021
Authors: Li, Wang
Article Type: Research Article
Abstract: The teaching of linguistics is limited by the influence of various factors, which leads to poor teaching effect, and the teaching process is difficult to evaluate. In order to improve the efficiency of linguistics teaching, this paper uses improved machine learning algorithms to construct a linguistics artificial intelligence teaching model. According to the teaching needs of linguistics, the efficiency of the teaching process is improved, and the teaching evaluation is performed, and the root cause analysis algorithm based on MCTS is optimized. Moreover, according to the frequent item set algorithm in data mining, a layered pruning strategy is proposed to …further reduce the search space and improve the efficiency of the model. In addition, this study combines with the comparative teaching experiment to study the efficiency of artificial intelligence models in linguistics teaching. The statistical results show that the model proposed in this paper has a certain effect. Show more
Keywords: Machine learning, artificial intelligence, linguistics, teaching reform
DOI: 10.3233/JIFS-189365
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3251-3262, 2021
Authors: Li, Bo | Su, Zheqian
Article Type: Research Article
Abstract: “College English teaching guide” puts in forth unique challenges and needs for College teaching skills of English. It is pressing to cultivate innovative talents with quality writing in English. Teaching in English, as a subject to check the mastery of students’ English knowledge. The successful instructional project of English writing is an assurance and support smooth growth of English writing. It can make education get double the efforts, and allow the students development.’ writing ability y, but in fact, the current situation of structural design of writing English in college is not optimistic. With the rise of “Web in addition …to”, varying backgrounds have experienced emotional changes. “Web in addition to training” has become a pattern of advancement, which has brought new chances and difficulties for the educating and learning of College English composition. This research first describes the research status of data mining and College English writing at places of abroad and input the future the content of research and methods of research. Taking college English writing teaching as the research object, the association rules algorithm in data mining is applied to analyze the correlation factors of students’ writing performance and provide decision-making suggestions for teachers’ teaching. Show more
Keywords: Data mining, English writing, teaching, association rules, internet plus
DOI: 10.3233/JIFS-189366
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3263-3269, 2021
Authors: Yangsheng, Zhang
Article Type: Research Article
Abstract: College physical education is too one-sided, which makes the teaching process evaluation meaningless. Based on this, based on neural network technology, this article combines artificial intelligence teaching system to build an artificial intelligence sports teaching evaluation model based on neural network. The artificial intelligence model starts from the process evaluation and the final evaluation. Moreover, it uses a recurrent neural network for data training and analysis, and introduces a new decoder to perform data processing, and introduces a simplified gated neural network internal structure diagram to build the internal structure of the model.In addition, this study designs a control experiment …to evaluate the performance of the model constructed in this study. The research results show that the artificial intelligence model constructed in this paper has a good effect in the performance prediction and evaluation of college sports students. Show more
Keywords: Artificial intelligence, physical education, performance prediction, evaluation system
DOI: 10.3233/JIFS-189367
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3271-3279, 2021
Authors: Huang, Jieru | Wang, Tao
Article Type: Research Article
Abstract: The modernization of our country has opened a new era, and the “Internet +” national strategy has gone deep into various areas of people’s livelihood. Faced with many changes in the new situation, a variety of emerging information technologies continue to integrate into the classroom, such as Baidu teaching, Whiteboard, IPAD, flipping classroom, and learning space and so on, which makes the teacher’s teaching method and organization form have very big changes. There is a certain “flip” in the classroom indeed. This study explores the connotation and characteristics of music intelligent teaching and the main factors that affect the formation …of music teachers’ intelligent teaching under the background of “Internet +” education. In this paper, the related strategies of the formation of wisdom teaching are applied through the design of the auxiliary system, in order to optimize the traditional teaching mode by making full use of the network technology, improve the teaching efficiency, and train more and more music talents for the country. Show more
Keywords: “Internet +”, music, wisdom teaching, information technology
DOI: 10.3233/JIFS-189368
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3281-3287, 2021
Authors: Li, Ruisheng
Article Type: Research Article
Abstract: Based on the analysis of the characteristics of artificial intelligence and agent, this paper discusses the feasibility of introducing Web services and intelligent agent technology into online teaching and learning and proposes a modern distance education system model based on artificial intelligence agent technology web. The architecture integrates the advantages of Agent technology and Web services. Starting from improving the shortcomings of the traditional Web-based distance teaching system, it strives to increase learners’ self-directed learning interest, monitor students’ emotions, and exchange knowledge between teaching agents. To realize students’ on-demand learning according to their aptitude, teachers’ teaching ultimately improve the system’s …flexibility, personalization, and artificial intelligence. Under the guidance of learning communities and other theories, construct learner model ontology inference rules. Based on the learner’s relationship characteristics, the knowledge domain that the learner is interested in is inferred, thus constructing an intelligent information retrieval system. Knowledge retrieval is realized quickly and accurately, thereby verifying the application of learner relationship characteristics in digital learning. Show more
Keywords: Artificial intelligence, agent technology, web distance education, system design
DOI: 10.3233/JIFS-189369
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3289-3299, 2021
Authors: Li, Zihao | Wang, Hejin
Article Type: Research Article
Abstract: Traditional physical education in colleges and universities is difficult to arouse students’ interest in sports, resulting in low activity participation rate and inability to exercise the body. How to effectively improve the effectiveness of physical education in colleges and universities has become one of the hot topics of most concern from all walks of life. In physical education, innovative teaching concepts and methods, teaching methods and processes, and teaching evaluation methods are all conducive to improving the classroom atmosphere of physical education and successfully improve the effectiveness of physical education. This article focuses on analyzing the current status of physical …education in colleges and universities. Based on the rapid development of artificial intelligence technology, how to improve the effectiveness of physical education is studied, and an experimental method is used to compare and analyze physical education in a college. The analysis results show that artificial intelligence-based physical education can obviously improve students’ strength quality, speed quality, endurance quality, and agility quality, which provides a more important reference and reference for improving the effectiveness of college physical education. Show more
Keywords: Artificial intelligence technology, college physical education, auxiliary teaching, effectiveness
DOI: 10.3233/JIFS-189370
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3301-3311, 2021
Authors: Cong, Canri | Fu, Dongmei
Article Type: Research Article
Abstract: The focus of this article is to explore the application of artificial intelligence in university sports information services based on the development trend of artificial intelligence technology. Research and analyze the characteristics and functions of new intelligent information service tools, and explore the effects of artificial intelligence in optimizing university sports information services from the three aspects of intelligent evolution information service, intelligent push information, and intelligent retrieval information, and the connotation of intelligent environment Analyze characteristics and technical support to promote the optimization and upgrading of university sports information services, research on the transformation of evaluation methods from manual …evaluation to intelligent evaluation, and from standardized evaluation to differential evaluation, and specifically analyze the connotation of intelligent evaluation and differential evaluation, Features and key technologies, analyze the general process of intelligent evaluation, and summarize the implementation suggestions for intelligent evaluation. And discuss the application of artificial intelligence in university sports information services from scientific decision-making and automated management. Show more
Keywords: Artificial intelligence, college sports, information service, optimization and upgrading
DOI: 10.3233/JIFS-189371
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3313-3324, 2021
Authors: Zhang, Jianye
Article Type: Research Article
Abstract: This article analyzes the reform of information services in university physical education based on artificial intelligence technology and conducts in-depth and innovative research on it. In-depth analysis of the relationship between big data and the development and application of information technology such as the Internet, Internet of Things, cloud computing, to clarify the difference and connection between big data, informatization and intelligence. Artificial intelligence will bring opportunities for changes in data collection, management decision-making, governance models, education and teaching, scientific research services, evaluation and evaluation of physical education in our university. At the same time, big data education management in …colleges and universities faces many challenges such as the balance of privacy and freedom, data hegemony, data junk, data standards, and data security, and they have many negative effects. In accordance with the requirements of educational modernization, centering on the goal of intelligent and humanized education management, it aims existing issues in college physical education management. Show more
Keywords: Artificial intelligence technology, college sports, educational information service, reform and innovation
DOI: 10.3233/JIFS-189372
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3325-3335, 2021
Authors: Guo, Qiang | Li, Bo
Article Type: Research Article
Abstract: The physical health test of college students is an important part of the school physical education work and an important part of the school education evaluation system. It is an educational method that promotes the healthy development of students’ physical fitness and encourages students to actively take physical exercises. It is an individual evaluation standard for students’ physical fitness. It is also one of the necessary conditions for students to graduate. In order to improve the physique and health of college students, this article first introduces functional exercise tests to comprehensively measure the exercise capacity of the main muscle groups …and joints of the human body, and integrate flexibility and strength qualities. Secondly, this article quantitatively studies the interaction law between the natural light environment comfort of sports training facilities and architectural design elements, and adopts appropriate dynamic optimization methods to improve the light environment quality of the sports space, thereby enhancing the visual comfort of the sports crowd in the stadium. Finally, the artificial intelligence technology is introduced, through the design of artificial intelligence system, intelligent data collection, and analysis. From the perspective of physical education, the functional exercise test based on artificial intelligence conforms to the essential meaning of the physical fitness test and helps to enhance the awareness of college students’ physical exercise. And the intelligent remote multimedia physical education system based on artificial intelligence makes the physical education process flexible, free from time and place restrictions, and can adopt different teaching strategies according to the different situations of students to implement personalized teaching. Show more
Keywords: AI, functional sports training, physical education
DOI: 10.3233/JIFS-189373
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3337-3345, 2021
Authors: Zhao, Zhe | Liu, Xingyu | She, Xi
Article Type: Research Article
Abstract: As an advanced training concept, functional physical training is gradually recognized by top athletes for its high training effect and low sports injury. Functional physical training should gradually develop from elite athletes to grassroots athletes, so as to lay a solid foundation for the development of competitive sports. Because particle filtering is susceptible to external factors in moving target tracking, this paper designs a method for sparse coding using local image blocks of the target, establishes a static “impression” and dynamic model for the appearance of the target. The tracking problem is regarded as a binary classification problem between the …foreground target and the background image. During the tracking process, the dual particle filter is implemented to alleviate the tracking drift, so that the algorithm can adaptively capture the changes in the target appearance At the same time, it can reduce the update caused by wrong positioning. The subjects’ FMS test and Y balance test have improved in varying degrees; the pressure distribution of the forefoot, arch, and heel tends to be rationalized, and the ratio of internal and external splayed feet has decreased. Experiments show that this particle filter moving target tracking scheme can adapt to changes in the environment and overcome the inflexibility of the global template when dealing with local changes in the target. Show more
Keywords: Functional sports training, sports target tracking, local sparse expression, particle filter
DOI: 10.3233/JIFS-189374
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3347-3359, 2021
Authors: Wang, Ju-An | Liu, Shen | Zhang, Xiping
Article Type: Research Article
Abstract: This article is based on artificial intelligence technology to recognize and identify risks in college sport. The application of motion recognition technology first need to collect the source data, store the collected data in the server database, collect the learner’s real-time data and return it to the database to achieve the purpose of real-time monitoring. It is found that in the identification of risk sources of sports courses, there are a total of 4 first-level risk factors, namely teacher factors, student factors, environmental factors, and school management factors, and a total of 15 second-level risk factors, which are teaching preparation, …teaching process, and teaching effect. When the frequency of teaching risks is low, the consequence loss is small. When the frequency of teaching risks is low, the consequences are very serious. Risk mitigation is the main measure to reduce the occurrence of teaching risks and reduce the consequences of losses. Show more
Keywords: Artificial intelligence, college sports, exercise risk, cognitive and recognition applications
DOI: 10.3233/JIFS-189375
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3361-3372, 2021
Authors: Wang, Hejin | Li, Zihao
Article Type: Research Article
Abstract: Recently, Intense training in specialized sport among colleges and universities has steadily improved. Although most sportspeople accept that some degree of expertise in sport is required to achieve the elite stage, there is controversy over risk recognition and identification of sports activities in colleges and universities to optimize future performance. There is concern that a young athlete can suffer from sports specialization before adolescence due to various risk factors such as injuries, social tension, and hypertension etc..,. Furthermore, PubMed and OVID are looking to discuss sports specialization and athlete experience-based consensus opinions and position statements based on Universities and Colleges. …Risk recognition and identification tools are developed to identify the locations of athletes within the specialization spectrum using Linear Structural Modeling (LSM). Here, a degree of sports expertise is needed to create elite skill levels to overcome risk factors that have been suggested in the linear model. In most sports, though, such accelerated preparation should be deferred until late adolescence to reduce risk factors. The psychological burden has been analyzed for recognition, and classification based on the case study has been firmly researched in this paper. Show more
Keywords: Novice athletes, social tension, colleges and universities, risk recognition, accelerated preparation
DOI: 10.3233/JIFS-189376
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3373-3383, 2021
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