Journal of Intelligent & Fuzzy Systems - Volume 40, issue 2

Authors: Senthil, S. | Ravi, K.

Article Type: Research Article

Abstract: This paper illustrates a new compilation of Micro-grid by distributed energy sources using three phase three -level Space vector multilevel inverter. In olden days only 3Φ inverter was designed and they were connected to the consumer with higher harmonics without automatic control feeding power to the consumer end. But this system we implemented three phase three level inverter was fed power to the consumer and also reduces the switching losses. I have connected three renewable sources are alike Wind-turbine, P.V - cell and Pico-Hydel generator model to increases the potential of power supply to a relatively small jumble of …people, an official of the economic lay of a locality. Furthermore costless new semiconductor technologies in the power switches beside the necessity of current on giant consummation inverters necessitate by Renewable-Energy-Systems (R.E.S) by reduced Total-Harmonic-distortion (T.H.D) in the spectrum of switching waveform have expanded the applications of Multi-level inverters. This system also includes M.P.P.T electronic control to operate maximum point of modules so, it is supplying maximal power to the consumer connected load according to the changes in solar-radiation and diffusive-temperature and intern increase the battery charging current. Show more

Keywords: Renewable-energy-sources, micro-grid, multilevel- inverter, space-vector-modulation, reactive power –compensation and M.P.P.T algorithm

DOI: 10.3233/JIFS-189256

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2647-2660, 2021

Authors: Murugaboopathi, G. | Gowthami, V.

Article Type: Research Article

Abstract: Privacy preservation in data publishing is the major topic of research in the field of data security. Data publication in privacy preservation provides methodologies for publishing useful information; simultaneously the privacy of the sensitive data has to be preserved. This work can handle any number of sensitive attributes. The major security breaches are membership, identity and attribute disclosure. In this paper, a novel approach based on slicing that adheres to the principle of k -anonymity and l -diversity is introduced. The proposed work withstands all the privacy threats by the incorporation of k-means and cuckoo-search algorithm. The experimental results with …respect to suppression ratio, execution time and information loss are satisfactory, when compared with the existing approaches. Show more

Keywords: Privacy preservation, slicing, k-anonymity, l-diversity

DOI: 10.3233/JIFS-189257

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2661-2668, 2021

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2669-2669, 2021

Authors: Yuan, X. | Elhoseny, M.

Article Type: Editorial

DOI: 10.3233/JIFS-189585

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2671-2671, 2021

Authors: Miao, Jianjun

Article Type: Research Article

Abstract: It is difficult for the intelligent teaching system in colleges to effectively predict student grade, which makes it difficult to formulate follow-up teaching strategies. In order to improve the effect of student grade prediction, this study improves the neural network algorithm, combines support vector machines to build a student grade prediction model, and uses PCA to reduce the dimensionality of the sample data. The specific operation is realized by SPSS software. Moreover, this study removes redundant information inside the input vector and compresses multiple features into a few typical features as much as possible. In addition, the research set a …control experiment to analyze the performance of the research model and compare the advantages and disadvantages of the classification prediction effect of traditional machine learning algorithms and neural network algorithms. Through experimental comparison, we can see that the model constructed in this paper has certain advantages in all aspects of parameter performance, and the prediction model proposed in this study has certain effects. Show more

Keywords: Support vector machine, neural network, student grade, prediction model

DOI: 10.3233/JIFS-189310

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2673-2683, 2021

Authors: Xu, Hesheng

Article Type: Research Article

Abstract: University legal education is of great significance to the personal development and social stability of college students. At present, there are certain problems in the traditional teaching system, which has led to inefficient university legal education. In order to improve the legal teaching effect of the university, based on machine learning and neural networks, this paper integrates and optimizes the original hardware and software and operation process, and further highlights the functions of interconnection and sharing, automatic sensing, real-time recording, interactive feedback, dynamic supervision, and intelligent analysis, which greatly facilitates the evaluation of teaching at all levels. In particular, this …study uses big data technology to conduct an intelligent analysis of data completeness, multimedia application rate, system execution, and average test scores, and scientifically evaluates the implementation of basic-level education systems and the effectiveness of education, which can effectively solve the problems of quantitative formalization and qualitative subjectivity of current education evaluation from a technical level. In addition, this study designs a control experiment to analyze the system performance. The research results show that the model proposed in this paper has a certain effect. Show more

Keywords: Machine learning, neural network, university law, education system

DOI: 10.3233/JIFS-189311

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2685-2696, 2021

Authors: Ding, Qinglong | Ding, Zhenfeng

Article Type: Research Article

Abstract: Sports competition characteristics play an important role in judging the fairness of the game and improving the skills of the athletes. At present, the feature recognition of sports competition is affected by the environmental background, which causes problems in feature recognition. In order to improve the effect of feature recognition of sports competition, this study improves the TLD algorithm, and uses machine learning to build a feature recognition model of sports competition based on the improved TLD algorithm. Moreover, this study applies the TLD algorithm to the long-term pedestrian tracking of PTZ cameras. In view of the shortcomings of the …TLD algorithm, this study improves the TLD algorithm. In addition, the improved TLD algorithm is experimentally analyzed on a standard data set, and the improved TLD algorithm is experimentally verified. Finally, the experimental results are visually represented by mathematical statistics methods. The research shows that the method proposed by this paper has certain effects. Show more

Keywords: TLD algorithm, improved algorithm, machine learning, competition features, feature recognition

DOI: 10.3233/JIFS-189312

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2697-2708, 2021

Authors: Fang, Chuanxin

Article Type: Research Article

Abstract: English Online teaching quality evaluation refers to the process of using effective technical means to comprehensively collect, sort and analyze the teaching status and make value judgments to improve teaching activities and improve teaching quality. The research work of this paper is mainly around the design of teaching quality evaluation model based on machine learning theory and has done in-depth research on the preprocessing of evaluation indicators and the construction of support vector machine teaching quality evaluation model. Moreover, this study uses improved principal component analysis to reduce the dimensionality of the evaluation index, thus avoiding the impact of the …overly complicated network model on the prediction effect. In addition, in order to verify that the model proposed in this study has more advantages in evaluating teaching quality than other shallow models, the parameters of the model are tuned, and a control experiment is designed to verify the performance of the model. The research results show that this research model has a certain effect on the evaluation of school teaching quality, and it can be applied to practice. Show more

Keywords: Support vector machine, decision tree, online teaching, teaching quality, feature recognition

DOI: 10.3233/JIFS-189313

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2709-2719, 2021

Authors: Hou, Qian | Li, Cuijuan | Kang, Min | Zhao, Xin

Article Type: Research Article

Abstract: English feature recognition has a certain influence on the development of English intelligent technology. In particular, the speech recognition technology has the problem of accuracy when performing English feature recognition. In order to improve the English feature recognition effect, this study takes the intelligent learning algorithm as the system algorithm and combines support vector machines to construct an English feature recognition system and uses linear classifiers and nonlinear classifiers to complete the relevant work of subjective recognition. Moreover, spectral subtraction is introduced in the front end of feature extraction, and the spectral amplitude of the noise-free signal is subtracted from …the spectral amplitude of the noise to obtain the spectral amplitude of the pure signal. By taking advantage of the insensitivity of speech to the phase, the phase angle information before spectral subtraction is directly used to reconstruct the signal after spectral subtraction to obtain the denoised speech. In addition, this study uses a nonlinear power function that simulates the hearing characteristics of the human ear to extract the features of the denoised speech signal and combines the English features to expand the recognition. Finally, this study analyzes the performance of the algorithm proposed in this study through comparative experiments. The research results show that the algorithm in this paper has a certain effect. Show more

Keywords: SVM, Intelligent algorithm, English features, feature recognition

DOI: 10.3233/JIFS-189314

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2721-2731, 2021

Authors: Yin, Zhimeng | Cui, Wei

Article Type: Research Article

Abstract: The results of data mining can be used to predict the physical health status of sports athletes and college sports students and provide physical fitness warnings, so that students can pay attention to physical health status and adjust their physical exercise status. Discrete Morse theory, as a powerful optimization theory, plays a big role in algorithm optimization. This paper combines data mining and discrete Morse theory to propose a grid clustering algorithm based on discrete Morse theory. Moreover, according to the theorem that the cell complex reaches the optimum when it has the smallest possible critical point, this study applies …the concept of critical points in the discrete Morse theory to optimize the grid clustering process to obtain clustering results. In addition, this study uses the improved C4.5 algorithm to analyze the physical fitness assessment results and obtains a valuable analysis of the physical fitness assessment results. Show more

Keywords: Discrete data, data mining, machine learning, sports

DOI: 10.3233/JIFS-189315

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2733-2742, 2021

Authors: Li, Na

Article Type: Research Article

Abstract: Text-to-voice conversion is the core technology of intelligent translation system and intelligent teaching system, which is of great significance to English teaching and expansion. However, there are certain problems with the characteristics of factors in the current text-to- voice conversion. In order to improve the efficiency of text-to- voice conversion, this study improves the traditional machine learning algorithm and proposes an improved model that combines statistical language, factor analysis, and support vector machines. Moreover, the model is constructed as a training module and a testing module. The model combines statistical methods and rule methods in a unified framework to make …full use of English language features to achieve automatic conversion of letter strings and phonetic features. In addition, in order to meet the needs of English text-to- voice conversion, this study builds a framework model, this study analyzes the performance of the model, and designs a control experiment to compare the performance of the model. The research results show that the method proposed in this paper has a certain effect. Show more

Keywords: Machine learning, improved algorithm, phonetic conversion, English, text-to-voice conversion

DOI: 10.3233/JIFS-189316

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2743-2753, 2021

Authors: Wang, Xingguo | Wu, Fan | Liu, Tao

Article Type: Research Article

Abstract: The eco-economic activity modeling is an effective method to analyze the eco-economic system. From the existing models, it can be seen that the disadvantages of eco-economic activity modeling are that the model evaluation accuracy is not high, and the system stability is poor. In order to improve the evaluation effect of the ecological economic activity, based on the machine learning algorithm, this study establishes a PNN evaluation model based on the probabilistic neural network classification principle. Moreover, in this study, a certain number of learning samples are generated by random interpolation of evaluation index standards, and then Matlab software is …used to simulate the training and test of the model, and the feasibility and effectiveness of the model are verified by statistical indicators. In addition, this study combines the actual case to analyze the performance of the model and analyze the test results by statistical analysis methods. The research results show that the model proposed in this study has certain effects and high stability. Show more

Keywords: Machine learning, ecological economy, economic activity, simulation analysis

DOI: 10.3233/JIFS-189317

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2755-2766, 2021

Authors: Zhang, Gaiqin

Article Type: Research Article

Abstract: At present, experts and scholars have conducted more research on the ability of colleges and universities to transform scientific and technological achievements. However, they pay more attention to the holistic research on the transformation of scientific and technological achievements in colleges and universities across the country, while rarely divide the research objects in detail. In order to improve the evaluation effect of scientific and technological achievements in colleges and universities, this paper builds a university science and technology achievement evaluation system based on machine learning and image feature retrieval on the basis of analyzing the needs of high-tech achievement evaluation. …The system has certain flexibility. Moreover, this study selects the appropriate network architecture based on the actual data and mission objectives of the high-tech achievement evaluation. In addition, this paper proposes a FT-GRU model of a gated recurrent unit network incorporating N nearest neighbor text, and a more stable model structure is obtained through system optimization. Finally, this study designs experiments to verify the performance of the model. The research results show that the university science and technology achievement evaluation system based on machine learning and image feature retrieval constructed in this study meets the expected goals and has certain practical significance. Show more

Keywords: Machine learning, image features, feature retrieval, scientific and technological achievements in colleges and universities

DOI: 10.3233/JIFS-189319

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2779-2789, 2021

Authors: Lin, Liu

Article Type: Research Article

Abstract: There is a certain subjectivity in the teaching evaluation process, which leads to a low accuracy of the intelligent scoring system. In order to promote the intelligent development of teaching evaluation, based on machine learning, this study briefly introduces the background and current status of teaching evaluation, and describes in detail the relevant algorithm principles of data analysis and modeling using data mining technology and machine learning methods. Moreover, this study describes the establishment process of the traditional classroom teaching evaluation system and uses the classification algorithm in machine learning in the construction of evaluation models to further improve the …scientificity and feasibility of teaching evaluation. In addition, in this study, empirical algorithm is used as the basic algorithm to evaluate teaching quality, and the topic word distribution obtained by joint model training is used as the original knowledge. Finally, this research analyzes the performance of this research system through a control experiment. The research results show that the scores of the research model are close to the standard manual scores and can provide a theoretical reference for subsequent related research. Show more

Keywords: Bayesian algorithm, improved algorithm, teaching evaluation, text features

DOI: 10.3233/JIFS-189320

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2791-2801, 2021

Authors: Zhao, Shujuan | Luo, Junqian | Wei, Shiqing

Article Type: Research Article

Abstract: Online classroom teaching is difficult to identify students’ learning status in real time. Therefore, we need to combine intelligent image recognition technology to analyze student status through eye movement features. This study solves the problem of inaccurate positioning of the initial position of the shape model in the process of eyelid matching through machine learning. Moreover, this study improves the algorithm and uses the AK-EYE model based on the combination of ASM algorithm and Kalman filtering to establish a local feature model for each feature point. According to the gray information in the normal direction of the feature point, the …local gray information is modeled. After training through the sample set to obtain the state model, the target eye can be searched, and the pose parameters can be determined. Finally, this study designs a control experiment to analyze the performance of the model proposed in this study. The research shows that the algorithm proposed in this paper has a high recognition accuracy and has a practical basis, which can be used as one of the subsequent classroom teaching system algorithms. Show more

Keywords: Machine learning, classroom recognition, student characteristics, eyeball characteristics

DOI: 10.3233/JIFS-189321

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2803-2813, 2021

Authors: Zhang, Rongbo | Zhao, Weiyu | Wang, Yixin

Article Type: Research Article

Abstract: There are different paradigms in educational technology. Under the background of big data era, data science, learning analysis and education have made great achievements. In the field of education under big data, all kinds of new paradigms are constantly emerging and have achieved very good results in actual education. In the era of education big data, how to fully tap the value of big data for online education practice, decision-making, evaluation and research, and how to avoid the risk of big data are important issues in the current education reform and development. This paper analyzes the application of the current …scientific paradigm in education, constructs the construction paradigm of online education evaluation model, and puts forward a new education concept in order to promote the development of the new paradigm of big data online education technology research. Applying this paradigm, a series of educational evaluation models are constructed from the macro, miso and micro levels, which play a positive role in the research, decision-making, practice and evaluation of related fields. Show more

Keywords: Big data, online education, scientific paradigm, smart classroom

DOI: 10.3233/JIFS-189322

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2815-2825, 2021

Authors: Lou, Feiyan | Kong, Depeng | Wang, Zhiwei

Article Type: Research Article

Abstract: Agricultural IoT technology realizes the technology of precise, intelligent, and scientific management of agricultural production. Accurate perception and efficient transmission of farmland data is the basis for precision and smart agriculture. Based on the consideration of WSN distributed monitoring sensor nodes, this paper designs a multi-core sensing agricultural Internet of Things monitoring system based on the low efficiency of existing single-core computing and the inability to adapt to massive sensing data node operations. Multi-core data fusion was simulated and analyzed. Firstly, a method for constructing key value subspaces based on logical landmarks is proposed. The node set maintained by the …subspace adds local physical location features to coordinate node discovery and routing. Compared with the traditional key value space, the subspace has a higher system priority, which makes the route local priority, thus realizing traffic localization. The simulation results show that the distributed agricultural network data aggregation algorithm based on multi-core perception can significantly reduce the energy consumption of sensor nodes in WSN, prolong the service life of WSN, and greatly improve the computational efficiency and data accuracy. Show more

Keywords: Agricultural IoT, multi-core sensing, single-core, WSN

DOI: 10.3233/JIFS-189323

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2827-2837, 2021

Authors: Wang, Juan | Zhao, Bo

Article Type: Research Article

Abstract: Based on the big data cloud computing platform with online teaching at the application scenario, the functional modules of the system are divided according to the user’s functional requirements for the system, and the system is briefly designed to determine the system architecture. The core functional modules of the system include an online experiment module, online classroom module, video course module, online examination module and basic function module. Using software engineering methods, the design process of the above functional modules is described, and the realization process of key functions is elaborated in detail. Taking into account the security requirements for …video transmission in the video course module, the streaming media on-demand technology based on the RTMP protocol is adopted. In order to meet the highly interactive requirements of the online classroom module, the rich Internet application development technology based on Flex4.0 is adopted. A distributed Docker cluster is used in the online experiment module to provide students with an experimental environment. Taking into account the future business growth of the system and the need for dynamic expansion, the load balancing technology based on Nginx reverse proxy is adopted. In the test phase, the black box test method was used to test the system’s functions, and the system was non-functionally tested on three aspects of compatibility, security, and system performance. The online teaching platform is designed in this article not only has basic function modules, but also starts from the safety performance of the system. When designing the system module, a safety function module is added, and the user data are encrypted using the MD5 algorithm, and through access control technology and system backup Ensure data security. This article combines the convenience of online learning with the practicality of computer courses to create a set of one-stop teaching platforms with rich functions entered on online experiments. The system has good support for the key links in the teaching process, and can effectively improve the learning efficiency of students and the teaching efficiency of teachers. Show more

Keywords: Cloud computing, big data, online education, interactive applications

DOI: 10.3233/JIFS-189324

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2839-2849, 2021

Authors: Bai, Xujing | Li, Jiajun

Article Type: Research Article

Abstract: In order to meet the rapid growth of educational data, to automate the processing of educational data business, improve operational efficiency and scientific decision-making, a statistical analysis platform for educational data is designed, and Hadoop-based education is designed from the conceptual model, logical model, and physical model. Data warehouse; designed and researched the storage of educational multidimensional data model; and then compared and tested the query efficiency and storage space of HBase and Hive in the Hadoop ecosystem based on educational big data, and used HBase+Hive integrated architecture to complete the education data The statistical analysis tasks and the function …of the educational data statistical analysis platform are transplanted to the educational big data platform based on Hadoop; the performance test of the conversion efficiency of educational big data in the ETL link is performed, which illustrates the effectiveness of the educational big data platform based on Hadoop. An object-oriented analysis and design method used to analyze and design the business requirements of teaching resource sharing services. From the perspective of managers and teachers, use case diagrams and use case description tables to define system business requirements. The role of teachers is further refined as the theme of teaching and research. Participants, participants in the subject teaching and research, initiators of simulation teaching research and development, participants, famous teachers, high-quality course judges and experts. The recording, accumulation, statistics and analysis of students’ learning behaviors will provide more valuable applications for school education. Show more

Keywords: Digitalization, educational resources, big data platform, visit statistics

DOI: 10.3233/JIFS-189325

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2851-2860, 2021

Authors: Xie, Juan | Yang, Yan

Article Type: Research Article

Abstract: This article first provides an overview of the Internet of Things technology, mainly analyzing the characteristics of the Internet of Things technology and the impact of core technologies on education reform; secondly, it studies the specific impact of the Internet of Things technology on the education reform of local applied universities, which is mainly divided into three On the one hand, it promotes the construction of smart campus, the second is the realization of personalized learning methods, and the third is the promotion of smart teaching. Subsequently, the intelligent teaching based on the intelligent robot platform was proposed and the …teaching demonstration was carried out. This research conducted an empirical study on third-year university students as the objects of teaching implementation. In the preparatory stage of teaching, the micro-curriculum of guided learning is produced, teaching activities are designed, and the study attitude and learner satisfaction questionnaire and interview outline are compiled. After the empirical teaching, analyzing the empirical results and related data, it is found that the application of intelligent robots in science courses can stimulate students’ interest in and enthusiasm in science courses; it can improve students’ creative thinking level and students’ learning satisfaction. Students’ perceived ease of use and perceived usefulness of the intelligent robot platform will affect students’ learning satisfaction, thereby affecting the teaching effect. Show more

Keywords: Internet of Things, college education, reform: teaching mode, evaluation system

DOI: 10.3233/JIFS-189326

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2861-2870, 2021

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