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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
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