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

Authors: Lanlan, Pan | Liangyu, Hu | Zhengya, Li

Article Type: Research Article

Abstract: English part-of-speech intelligent recognition is the scientific and technological basis for the development of intelligent speech systems. The difficulty in the current English speech recognition system lies in the recognition of English parts of speech. In order to improve the effect of English part-of-speech recognition, this study builds the language rules and morphological models of English morphological forms based on machine learning algorithms. Moreover, this study proposes a stemming extraction algorithm and a syllable division algorithm based on English characteristic rules. By studying basic phrases in English, this study analyzes the compositional structure of phrases, and determines the basic phrase …structure and composition rules of English such as noun, verb, and adjective. In addition, this research studies the basic English phrase recognition algorithm based on the rule method and the analysis of basic phrase ambiguity resolution. Finally, this study designs a control experiment to analyze the performance of the algorithm proposed in this paper model and confirm the classification algorithm. The research results show that the algorithm proposed in this paper has a certain practical effect. Show more

Keywords: Machine learning, prediction algorithm, English, part-of-speech recognition, algorithm improvement

DOI: 10.3233/JIFS-189236

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2409-2419, 2021

Authors: Chonggao, Pang

Article Type: Research Article

Abstract: Classroom student behavior recognition has important guiding significance for the development of distance education strategies. At present, the accuracy of students’ classroom behavior recognition algorithms has problems. In order to improve the effect of distance education student status analysis, this study combines the traditional clustering analysis algorithm and the random forest algorithm to improve the traditional algorithm and combines the human skeleton model to identify students’ classroom behavior in real time. Moreover, this research combines with the needs of students’ classroom behavior recognition to build a network topology model. The error rate of feature reconstruction using spatio-temporal features is lower …than that of a single feature. Through experiments, this study verifies the effectiveness of the extracted spatial angle features based on the human skeleton model. The results of algorithm performance test show that the proposed algorithm network structure is superior to the network structure of single feature extraction algorithm. Show more

Keywords: Cluster analysis, random forest, classroom behavior, feature recognition, student behavior

DOI: 10.3233/JIFS-189237

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2421-2431, 2021

Authors: Dongmei, Li

Article Type: Research Article

Abstract: English text-to-speech conversion is the key content of modern computer technology research. Its difficulty is that there are large errors in the conversion process of text-to-speech feature recognition, and it is difficult to apply the English text-to-speech conversion algorithm to the system. In order to improve the efficiency of the English text-to-speech conversion, based on the machine learning algorithm, after the original voice waveform is labeled with the pitch, this article modifies the rhythm through PSOLA, and uses the C4.5 algorithm to train a decision tree for judging pronunciation of polyphones. In order to evaluate the performance of pronunciation discrimination …method based on part-of-speech rules and HMM-based prosody hierarchy prediction in speech synthesis systems, this study constructed a system model. In addition, the waveform stitching method and PSOLA are used to synthesize the sound. For words whose main stress cannot be discriminated by morphological structure, label learning can be done by machine learning methods. Finally, this study evaluates and analyzes the performance of the algorithm through control experiments. The results show that the algorithm proposed in this paper has good performance and has a certain practical effect. Show more

Keywords: Machine learning, English, text-to-speech conversion, improved algorithm, simulation

DOI: 10.3233/JIFS-189238

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2433-2444, 2021

Authors: Lin, Liu

Article Type: Research Article

Abstract: The difficulty of knowledge point recommendation based on the learning diagnosis model lies in how to perform feature recognition and selection of recommended knowledge points. At present, the recommendation system has certain problems in the accuracy of recommended knowledge points. Based on this, this study mainly studies the personalized problem recommendation of middle school students in the field of education. Moreover, this study takes the answer records of students’ exercises as data, and combines the characteristics of the field of education to propose an exercise recommendation algorithm based on hidden knowledge points and an exercise recommendation method based on the …decomposition of student exercise weight matrix. In addition, in order to verify the effectiveness of this research algorithm, this paper selects the accuracy rate and recall rate as evaluation indicators to analyze the recommendation results of this algorithm and the current more advanced CF algorithm, and the statistical experiment results are drawn into charts. The research results show that the method proposed in this paper has certain advantages and can be used as one of the subsystems of the learning system. Show more

Keywords: Text vector model, support vector machine, learning information, personalized recommendation

DOI: 10.3233/JIFS-189239

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2445-2455, 2021

Authors: Qianna, Sun

Article Type: Research Article

Abstract: The intelligent evaluation of classroom teaching quality is one of the development directions of modern education. At present, some teaching quality evaluation models have accuracy problems, and the evaluation process is affected by a variety of interference factors, which leads to inaccurate model results, and it is impossible to find out the specific factors that affect teaching. In order to improve the accuracy of classroom teaching quality evaluation, this study improves RVM based on the method of feature extraction and empirical modal decomposition of ACLLMD method, and establishes classroom theoretical teaching quality evaluation model and experimental teaching quality evaluation model …based on RVM algorithm. Moreover, this study uses test data to analyze the accuracy and reliability of the evaluation results to verify the feasibility and reliability of the new method. In addition, this study verifies the reliability of this algorithm by comparing with the manual scoring results. The research results show that RVM can be used to construct classroom theory teaching quality evaluation models and experimental teaching quality evaluation models with high accuracy and good reliability. Show more

Keywords: Improved algorithm, neural network, path sequencing, network teaching, knowledge recommendation

DOI: 10.3233/JIFS-189240

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2457-2467, 2021

Authors: Wenjuan, Zhang

Article Type: Research Article

Abstract: The traditional English examination and the current examination system have been unable to meet the needs of the education industry for English examinations. In view of this, based on the neural network algorithm, this study proposes a hierarchical network management model from the user’s perspective. Based on the in-depth study of the neural network, this study combined with the network performance characteristics of large data volume, complex data to propose a new BP neural network algorithm. By dynamically changing the momentum factor and learning rate, the algorithm has greatly improved the accuracy and stability of the error. In addition, this …study proposes a user perception prediction model, and the model is continuously trained on the model based on the improved BP neural network algorithm and the monitored network performance. In order to study the performance of the research model, a control experiment is designed to analyze the performance of the model. The research results show that the intelligent model and algorithm proposed in this paper are completely feasible and effective. Show more

Keywords: Neural network, English, hierarchical model, improved algorithm

DOI: 10.3233/JIFS-189241

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2469-2480, 2021

Authors: Qianyun, Yang | Xiaoyan, Wang

Article Type: Research Article

Abstract: The increasing complexity of the financial system has increased the uncertainty of the market, which has led to the complexity of the evolution of limited rational investor behavior decisions. Moreover, it also has a negative effect on the market and affects the development of the real economy and social stability. In view of the interconnected characteristics of various elements presented in financial complexity, based on complex network theory, Bayesian learning theory and social learning theory, this study systematically describes the behavioral decision-making mechanism of individual investors and institutional investors from the perspective of network learning. In addition, this study builds …an evolutionary model of investor behavior based on Bayesian learning strategies. According to the results of the horizontal and vertical bidirectional studies simulated by experiments, we can see that the method proposed in this study has a certain effect on the evaluation and decision support of stock market investment. Show more

Keywords: Bayesian learning, stock market, investment behavior, behavior simulation

DOI: 10.3233/JIFS-189242

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2481-2491, 2021

Authors: Pengyu, Wang | Wanna, Gao

Article Type: Research Article

Abstract: Basketball player detection technology is an important subject in the field of computer vision and the basis of related image processing research. This study uses machine learning technology to build a basketball sport feature recognition model. Moreover, this research mainly takes the characteristic information of basketball in the state of basketball goals as the starting point and compares and analyzes the detection methods by detecting the targets in the environment. By comprehensively considering the advantages and disadvantages of various methods, a method suitable for the subject is proposed, namely, a fast skeleton extraction and model segmentation method. The fitting effect …of this method, whether in terms of compactness or quantity, has greater advantages than traditional bounding boxes, and realizes the construction of dynamic ellipsoidal bounding boxes in a moving state. In addition, this study designs a controlled trial to verify the analysis of this research model. The research results show that the model proposed in this paper has certain effects and can improve practical guidance for competitions and basketball players training. Show more

Keywords: Machine learning, basketball, simulation model, basketball player

DOI: 10.3233/JIFS-189243

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2493-2504, 2021

Authors: Bu, Suhua

Article Type: Research Article

Abstract: In the era of the Internet of Things, smart logistics has become an important means to improve people’s life rhythm and quality of life. At present, some problems in logistics engineering have caused logistics efficiency to fail to meet people’s expected goals. Based on this, this paper proposes a logistics engineering optimization system based on machine learning and artificial intelligence technology. Moreover, based on the classifier chain and the combined classifier chain, this paper proposes an improved multi-label chain learning method for high-dimensional data. In addition, this study combines the actual needs of logistics transportation and the constraints of the …logistics transportation process to use multi-objective optimization to optimize logistics engineering and output the optimal solution through an artificial intelligence model. In order to verify the effectiveness of the model, the performance of the method proposed in this paper is verified by designing a control experiment. The research results show that the logistics engineering optimization based on machine learning and artificial intelligence technology proposed in this paper has a certain practical effect. Show more

Keywords: Machine learning, artificial intelligence, logistics, optimization

DOI: 10.3233/JIFS-189244

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2505-2516, 2021

Authors: Chen, Haixia

Article Type: Research Article

Abstract: Innovation and entrepreneurship are an important support for social and economic development in the new era, and it is also the key to the cultivation of practical talents in universities. In order to mine the effective information of innovation and entrepreneurship data, based on the neural network algorithm, this paper combines the bat algorithm to construct a data processing model to obtain an artificial intelligence innovation and entrepreneurship system with data analysis capabilities. Moreover, this study combines with actual needs to improve the algorithm, effectively eliminate the noise existing in the data, eliminate the interference of invalid data on the …judgment ability of the system model, and choose the best denoising algorithm through comparison and verification of various algorithms. In order to verify the model proposed in this paper, the data is input into this research model by collecting data in a college survey, so as to verify and analyze the performance of the model. The research results show that the artificial intelligence system proposed in this paper has good performance and has certain practical value. Show more

Keywords: Artificial intelligence, neural network, improved algorithm, innovation and entrepreneurship

DOI: 10.3233/JIFS-189245

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2517-2528, 2021

Authors: Cui, Yan | Zhang, Lijun | Hou, Yumei | Tian, Ge

Article Type: Research Article

Abstract: At present, there is a certain lag in the construction of the service platform of the smart home pension system in my country, which does not reflect the use characteristics of the elderly. In order to improve the reliability of the smart service system for the elderly, this research builds a smart home care service platform based on machine learning and wireless sensor networks around the state of the elderly’s home life, disease stage, physical state, and intellectual state. Moreover, after comparing the advantages and disadvantages of several wireless sensor communication network technologies and in-depth understanding of communication principles and …network topology, the overall design of the system is proposed. In addition, this study combines the design requirements of the system to optimize and improve the wearable physiological parameter collection system and focuses on the design and implementation of the hardware and software of the physiological parameter collection module in the construction of the new system platform. Finally, this study analyzes the performance of the model in this study through controlled trials. The results of the study show that the platform constructed in this paper is effective. Show more

Keywords: Machine learning, wireless sensor, smart home, pension service

DOI: 10.3233/JIFS-189246

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2529-2540, 2021

Authors: Huang, Zhaokun | Liu, Guanjun

Article Type: Research Article

Abstract: The fundamental solution to the problems of college students’ employment is to encourage college students to start their own businesses. Only by using entrepreneurship to promote employment can the real solution of China’s higher education employment problems be truly solved. Aiming at the current situation of college students’ entrepreneurship and employment, this paper builds a model system suitable for college students’ employment and entrepreneurship forecast and guidance through artificial intelligence algorithms and fuzzy logic models. The diversity-enhanced employment recommendation system developed in this paper uses the MVC three-tier architecture. Moreover, the diversity-enhanced employment recommendation system designed in this paper provides …two recommendation methods: individual diversity optimization and overall diversity optimization, which takes into account the relationship between students’ personal interests and employment work. In addition, the system uses the basic idea of user-based collaborative filtering. Finally, this paper designs a control experiment to analyze the performance of this research model. The research shows that the entrepreneurship employment forecast and guidance model constructed in this paper has a certain effect. Show more

Keywords: Artificial intelligence, fuzzy logic, college student employment, entrepreneurship, model

DOI: 10.3233/JIFS-189247

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2541-2552, 2021

Authors: Ran, Li

Article Type: Research Article

Abstract: Government subsidies have an important impact on the development of high-interest technology companies and technological innovation. In order to study the relationship between government investment and the development of high-tech enterprises and technological innovation, based on artificial intelligence and fuzzy neural network, this paper builds an analysis model based on artificial intelligence and fuzzy neural network. According to the operation of each loop, this study designs a scheduling strategy that dynamically allocates network utilization according to the dynamic weight of the loop, and periodically changes the sampling period of the system, so that the system can not only run stably …but also maximize the use of limited bandwidth. The network resource allocation module allocates the available network bandwidth of each control loop according to the dynamic weight of each loop, and the sampling period calculation module calculates a new sampling period based on the allocated network utilization rate. In addition, in this study, the performance of the model constructed in this paper is analyzed through empirical analysis. The results of the study show that the model constructed in this paper is effective. Show more

Keywords: Artificial intelligence, fuzzy algorithm, government subsidies, high-tech, investment

DOI: 10.3233/JIFS-189248

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2553-2563, 2021

Authors: Ma, Wenjuan | Zhao, Xuesi | Guo, Yuxiu

Article Type: Research Article

Abstract: The application of artificial intelligence and machine learning algorithms in education reform is an inevitable trend of teaching development. In order to improve the teaching intelligence, this paper builds an auxiliary teaching system based on computer artificial intelligence and neural network based on the traditional teaching model. Moreover, in this paper, the optimization strategy is adopted in the TLBO algorithm to reduce the running time of the algorithm, and the extracurricular learning mechanism is introduced to increase the adjustable parameters, which is conducive to the algorithm jumping out of the local optimum. In addition, in this paper, the crowding factor …in the fish school algorithm is used to define the degree or restraint of teachers’ control over students. At the same time, students in the crowded range gather near the teacher, and some students who are difficult to restrain perform the following behavior to follow the top students. Finally, this study builds a model based on actual needs, and designs a control experiment to verify the system performance. The results show that the system constructed in this paper has good performance and can provide a theoretical reference for related research. Show more

Keywords: Computer, artificial intelligence, neural network, education

DOI: 10.3233/JIFS-189249

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2565-2575, 2021

Authors: Qu, Xiaojuan

Article Type: Research Article

Abstract: Aiming at the actual problems encountered in the specific poverty alleviation work, this article designs a management system specifically designed for poverty alleviation workers to solve poverty alleviation data sharing and online editing and uploading of poverty alleviation logs. Based on the neural network and network characteristics, a system model is constructed, and the application of structural disturbance theory in dynamic networks is studied. Moreover, in this study, the dynamic change information between time-series networks is taken into account for structural disturbances. By combining structural disturbances and local topology, a new similarity measurement method suitable for dynamic networks is proposed. …In addition, this study proposes an algorithm based on evolutionary clustering and density clustering to detect the structure of dynamic communities. Finally, this study compares the proposed method with the classic method in the artificial network and the real network and analyzes the performance of the research model through data analysis. The research results show that the model constructed in this paper has good performance. Show more

Keywords: Neural network, network characteristics, ecological constraints, farmers, poverty alleviation

DOI: 10.3233/JIFS-189250

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2577-2588, 2021

Authors: Xin, Wu | Daping, Qiu

Article Type: Research Article

Abstract: The inheritance and innovation of ancient architecture decoration art is an important way for the development of the construction industry. The data process of traditional ancient architecture decoration art is relatively backward, which leads to the obvious distortion of the digitalization of ancient architecture decoration art. In order to improve the digital effect of ancient architecture decoration art, based on neural network, this paper combines the image features to construct a neural network-based ancient architecture decoration art data system model, and graphically expresses the static construction mode and dynamic construction process of the architecture group. Based on this, three-dimensional model …reconstruction and scene simulation experiments of architecture groups are realized. In order to verify the performance effect of the system proposed in this paper, it is verified through simulation and performance testing, and data visualization is performed through statistical methods. The result of the study shows that the digitalization effect of the ancient architecture decoration art proposed in this paper is good. Show more

Keywords: Neural network, image features, ancient architecture, decorative arts, system

DOI: 10.3233/JIFS-189251

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2589-2600, 2021

Authors: Kun, Xu | Wang, Zhiliang | Zhou, Ziang | Qi, Wang

Article Type: Research Article

Abstract: For industrial production, the traditional manual on-site monitoring method is far from meeting production needs, so it is imperative to establish a remote monitoring system for equipment. Based on machine learning algorithms, this paper combines artificial intelligence technology and Internet of Things technology to build an efficient, fast, and accurate industrial equipment monitoring system. Moreover, in view of the characteristics of the diverse types of equipment, scattered layout, and many parameters in the manufacturing equipment as well as the complexity of the high temperature, high pressure, and chemical environment in which the equipment is located, this study designs and implements …a remote monitoring and data analysis system for industrial equipment based on the Internet of Things. In addition, based on the application scenarios of the actual aeronautical weather floating platform test platform, this study combines the platform prototype system to design and implement a set of strong real-time communication test platform based on the Windows operating system. The test results show that the industrial Internet of Things system based on machine learning and artificial intelligence technology constructed in this paper has certain practicality. Show more

Keywords: Machine learning, artificial intelligence, industry, internet of things

DOI: 10.3233/JIFS-189252

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2601-2611, 2021

Authors: Caiqian, Zhang | Xincheng, Zhang

Article Type: Research Article

Abstract: The existing stand-alone multimedia machines and online multimedia machines in the market have certain deficiencies, so they cannot meet the actual needs. Based on this, this research combines the actual needs to design and implement a multi-media system based on the Internet of Things and cloud service platform. Moreover, through in-depth research on the MQTT protocol, this study proposes a message encryption verification scheme for the MQTT protocol, which can solve the problem of low message security in the Internet of Things communication to a certain extent. In addition, through research on the fusion technology of the Internet of Things …and artificial intelligence, this research designs scheme to provide a LightGBM intelligent prediction module interface, MQTT message middleware, device management system, intelligent prediction and push interface for the cloud platform. Finally, this research completes the design and implementation of the cloud platform and tests the function and performance of the built multimedia system database. The research results show that the multimedia database constructed in this paper has good performance. Show more

Keywords: Internet of things, cloud service platform, multimedia system, database

DOI: 10.3233/JIFS-189253

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2613-2624, 2021

Authors: Gunjal, Sheetal D. | Raut, Rajeshree D. | Wagh, Abhay

Article Type: Research Article

Abstract: The paper presents integration of Discrete Wavelet Cosine Transform technique and Bacterial Foraging Algorithm (BFO) for the development and optimization of speech coder. It is depicted how by filtering the limited number of high energy components of transformed coefficients with parallel programming can maintain the speech signal quality in coding over wide range of bit rates. The performance of existing and proposed speech coding techniqueattributes such as compression ratio, coding delay, computational complexity and quality of reconstructed speech is examined for multiple bit rates and compared with other existing speech coding techniques in Matlab environment. The result showsimprovement in performancewith …respect to all attributes at the cost of increase in complexity. Show more

Keywords: Speech coder attributes, Discrete Wavelet Cosine Transform, Bacterial Foraging Optimization, Software Defined Radio

DOI: 10.3233/JIFS-189254

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2625-2635, 2021

Authors: Renjini, G.S. | Deepa, T.

Article Type: Research Article

Abstract: DC-DC converters are widely used in many consumer electronic devices such as computers, medical equipment, battery chargers, cellular phones and many Industrial drives. These electronic devices require different voltage levels which is supplied from battery or some external supply. In multiple battery mission voltage decays as its stored energy is drained and requires large saving space. The switched DC-DC converters overcome these drawbacks and also regulate the output voltage for different power levels efficiently. This paper elaborates the structure of Luo converter with optimized PI controller. Positive Output Elementary Luo Converter (POELC) is designed for boost operation by choosing the …appropriate duty cycle. The PI controller parameters are optimized using Cuckoo and Crow search algorithms. The proposed control methods are investigated for the transient and steady state region. The sensitivity of these controllers to supply load and line disturbances are also studied along with the servo response are presented. The controller incorporates a Luo converter is evaluated in terms of Integral Time Square Error (ITSE) and Integral Time Absolute Error. Dynamic modelling of the power converter is derived by using state space averaging method. The simulation model of the Luo converter with its control circuit is implemented in MATLAB/SIMULINK. Experimental result shows that Cuckoo PI controller has significantly performance improvement in comparison with both the conventional and Crow PI controller. Show more

Keywords: Positive output elementary luo converter (POELC), cuckoo search optimization, crow search optimization, proportional – integral (PI), ziegler nichols (ZN), pade routh approximation

DOI: 10.3233/JIFS-189255

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2637-2645, 2021

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