Journal of Intelligent & Fuzzy Systems - Volume 37, issue 5

Authors: Kong, Fei | Wang, Yumin

Article Type: Research Article

Abstract: At present, there is less software related to sport technical behavior recognition, and there are few studies on the classification and identification of detailed actions. By introducing computer technology to analyze the efficiency and regularity of sports, not only the characteristics of athletes can be excavated, but also the visibility and dynamic tracking of sport training can be provided. The process of sports education is a fast and complex systematic process. Through the interactive system of physical education, we can use different methods to collect sports data and make a comparative analysis of athletes’ movements. Through the data mining of …the relationship between athletes’ physiological indexes and sports load, the unreasonable link in sports training can be avoided. Also, in sports training, we can use computer vision and modern biomechanics to construct a virtual sports education situation. With the classification accuracy as the fitness function, this paper collects the data through the network database, and returns the corresponding sport training parameters on this basis. The results showed that the accuracy of the model was nearly 98%, which met the actual demand. Therefore, the development of sports education assistant system can provide strong support for the process control of sports training and education. Show more

Keywords: Support vector, improved model, computer interactive system, recognition algorithm

DOI: 10.3233/JIFS-179200

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6165-6175, 2019

Authors: Bo, Wang | Tianyu, Fan | Zhiyong, Li | Xiangtian, Nie

Article Type: Research Article

Abstract: There is little research on the relationship between financial innovation and economic growth, and the research on the synergy between the two is basically blank. Based on this, from a general perspective, through constructing the corresponding subsystems in combination with financial innovation and economic growth, establishing the corresponding synergy model, and discovering the synergy development relationship by studying the degree of synergy in the past period, this study builds a BP neural network simulation model to predict the degree of synergy between financial innovation and economic growth in 2018 on the basis of practice. At the same time, this study …compares it with the actual situation to verify its effectiveness. Through analysis, the research model has certain effectiveness, which is basically consistent with the actual development trend. The research proposes that the main trend of financial innovation from the perspective of generalized virtual economy is Internet finance. This is the first time to study this issue from a new perspective, theory and method, which expands the existing research results. Show more

Keywords: BP neural network, financial innovation, economic growth, synergy

DOI: 10.3233/JIFS-179201

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6177-6189, 2019

Authors: Li, Tuojian | Sun, Jinhai | Zhang, Xianliang | Wang, Lei | Zhu, Penglei | Wang, Ning

Article Type: Research Article

Abstract: Competitive sports require athletes to operate in real time, and there are many uncertainties. At present, there are few applications of artificial intelligence in the prediction of competitive sports, and the relevant literature about fitness motivation is rare. Based on this, this study is based on the machine learning algorithm and uses the support vector machine to build the competitive sports model and fitness motivation evaluation. At the same time, this study combines the actual situation to construct a corresponding factor analysis model for racing sports, and this factor analysis is a combination of data mining and machine learning. Only …by adopting appropriate measures can students’ motivation of physical fitness be effectively fostered and stimulated, their active participation in physical exercise and lifelong fitness habits be fostered. On the basis of traditional SVM method, PCA-SVM model is constructed to further improve the prediction accuracy and validity of fitness motivation. In this paper, the principal components of eight kinds of operation behavior are extracted; fitness motivation is not only the direct reason for college students to participate in fitness exercise, but also the motive force of fitness behavior. Grid Search algorithm is selected to optimize the parameters of SVM. The recognition rate of Grid Search-SVM is 94.79%, and satisfactory results are obtained. Show more

Keywords: Support vector machine, racing sports, regression model, GA-SVM algorithm

DOI: 10.3233/JIFS-179202

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6191-6203, 2019

Authors: Guangjing, Li | Cuiping, Zhang

Article Type: Research Article

Abstract: At present, artificial intelligence for sports static image recognition is mostly in the action judgment stage, but less analysis on the action detail stage. Based on this, based on machine learning, this study uses static images and video sequences as carriers to improve traditional algorithm research and to perform motion gesture recognition. Through performance analysis, this paper explores the traditional algorithm and uses parameter analysis to improve the feature extraction and classification of traditional algorithms. Moreover, this paper uses the multi-scale feature approximation calculation method to improve the speed of the algorithm to extract features, and the algorithm is tested …using the UCF motion data set and the self-created motion data set. In addition, this paper obtains representative motion video through data collection to test the effectiveness of the proposed algorithm. The research shows that the proposed algorithm has good performance and can provide theoretical reference for subsequent related research. Show more

Keywords: Machine learning, sports, static image, gesture recognition

DOI: 10.3233/JIFS-179203

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6205-6215, 2019

Authors: Wei, Cheng | Dan, Li

Article Type: Research Article

Abstract: Estimating the compensation risk of agricultural insurance is a hotspot of current research. The related research mainly focuses on the calculation and simulation of catastrophe risk that agricultural insurance may face. On the whole, the compensation risk of agricultural insurance mainly comes from the agricultural disasters, especially the agro meteorological disasters. Compared with property insurance, the overall compensation rate of agricultural insurance is much higher than that of property insurance, so agricultural insurance belongs to high-risk business operation. In the research, the support vector machine is used as the research technology, and the forecast model corresponding to the insurance market …is constructed. At the same time, this paper constructs SVM prediction model and VAR-based SVM prediction model. Finally, the prediction accuracy of the SVM prediction model and the VAR-based SVM prediction model are compared and analyzed. The research shows that the prediction accuracy of VAR-based SVM prediction model is higher, that is, it is easier to draw near-realistic prediction results based on parameter optimization. This paper summarizes the research, puts forward its inadequacies and merits, and provides theoretical reference for subsequent related research. Show more

Keywords: Parameter optimization, machine learning, agricultural insurance, forecast model

DOI: 10.3233/JIFS-179204

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6217-6228, 2019

Authors: Xu, Wanxiao | Ding, Mingjie

Article Type: Research Article

Abstract: The accelerated development of urbanization in China started with economic globalization and industrialization, and also in the process of economic system transition. Generally speaking, urbanization is an important indicator of a region’s economic development and social development. Urbanization equity is an important direction of sustainable economic and social development. From the economic dimension, urbanization can promote division of labor, specialization and accumulation of human capital through agglomeration effect. This paper analyzes the social equity and urbanization by using fuzzy logic and factor analysis model. Under the condition of market economy, migrant workers have no competitive advantage in the labor market …because of their low educational level. At the same time, the treatment of migrant workers in social security, cultural education and economic welfare is lower than that of urban residents. Under the unbalanced economic development reality, the economic absorption effect leads to the migrant workers rushing to the developed big cities. The results shows that by taking the dimensions of social justice of the rural migrant worker as the independent variable, psychological urbanization for the dependent variable, the regression Equation of F value is 90.424, P  = 0.000, less than 0.05 level of significance. Also, we make correlation analysis on all factors of social justice and urbanization. The experimental results show the effectiveness of proposed method. Green building is the development of sustainable development concept in architectural field. While the construction industry has brought great benefits to the development of national economy, its high investment, high pollution and inefficient development mode has also produced a huge energy load. Therefore, from the perspective of environmental and economic sustainability, the development of green buildings is particularly important. In this paper, the author makes economic benefit analysis of green building based on fuzzy logic and bilateral game model. By introducing such factors as economic benefits, cognition and government policies, this paper construct an evolutionary game model, which provides a basis for improving the economic benefits of green buildings. The results show that the first factor affecting enterprise decision-making is the incremental profit of green building developers, followed by the government’s incentive policy. After the evolution of the market, the final strategic choice will be stabilized to higher economic benefits. Generally speaking, green buildings need to effectively control incremental costs and consider scale benefits. Through management efficiency innovation and policy stimulation, the problems of huge investment cost and long payback period can be solved, so as to improve the economic benefits of green building development. Show more

Keywords: Urbanization rate, social security, fuzzy model, factor analysis

DOI: 10.3233/JIFS-179205

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6229-6240, 2019

Authors: Liwei, Sun

Article Type: Research Article

Abstract: At present, the application of artificial intelligence in the identification and classification of sports technology is still relatively small, and it is difficult to effectively improve the training and competition quality of athletes. Based on this, this study takes badminton as an example for analysis. Moreover, based on the complexity and multi-deformation of this motion, this study uses machine learning as the basic algorithm to design a real-time classification algorithm for badminton action. At the same time, this paper improves the traditional algorithm, designs an improved training model, and verifies the effectiveness of the design algorithm by experimental method. In …addition, this paper constructs a feature statistics and pace training system with the support of machine learning algorithms through statistical analysis and statistical badminton technical features and realizes the intelligentization of badminton batting action classification and recognition. Finally, this paper designs a comparative test for system functional testing. The system test shows that the system can effectively improve the action classification and recognition effect and can provide theoretical reference for subsequent related research. Show more

Keywords: Machine learning, badminton, motion recognition, action classification

DOI: 10.3233/JIFS-179206

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6241-6252, 2019

Authors: Yuan, Xiaoyi

Article Type: Research Article

Abstract: The lack of effective evaluation of online education is a worldwide malpractice, and it is impossible to help students improve the correctness of online learning choices through existing reviews. Based on the current mainstream sentiment lexicon and text sentiment analysis, the authors use machine learning method to analyze the sentiment orientation of the legal course review text, through method that combines PMI and SVM. At the same time, this paper uses LibSVM tool to train and predict data, collect and pre-process data through network data collection, and, based on traditional algorithms, propose improved experimental scheme based on their respective advantages …and disadvantages. In addition, the model proposed in this study is used to classify and process the emotional text, and the two methods are combined to obtain the final result. Finally, this paper combines experiments to analyze the performance of the comprehensive model proposed in this study. The research shows that the classification effect of the text sentiment analysis of model is good, it can be applied to practice, and it can provide theoretical reference for subsequent related research. Show more

Keywords: Support vector machine, algorithmic optimization, online course, data network

DOI: 10.3233/JIFS-179207

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6253-6263, 2019

Authors: Xiaolong, Zhang

Article Type: Research Article

Abstract: Athletes have a large amount of video information, so how to capture effective information is the key to improving athletes’ training efficiency and improving the quality of the game. From the perspective of deep learning, this study analyzes and improves traditional algorithm models based actual needs, and jointly learns multi-scale features. At the same time, in view of the problem of over-fitting in the model training process, this study uses the sparse pyramid pool strategy to adjust the pool parameterization process and reduce the complexity of feature description. In addition, the research designs experiment to analyze the performance of the …improved algorithm model and select the appropriate database to analyze the recognition effect of the algorithm model. The research shows that the algorithm of this research has a certain improvement in the recognition effect of athletes, and the recognition effect matching the artificial design features can be obtained, and it can provide theoretical reference for subsequent related research. Show more

Keywords: Deep learning, convolution algorithm, motion recognition, database management, deep learning

DOI: 10.3233/JIFS-179208

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6265-6274, 2019

Authors: Chaoming, Liang

Article Type: Research Article

Abstract: Ball sports have great variability in the game and the intelligent control of the rules of ball movement can effectively improve the training effect of athletes. However, the current research on artificial intelligence of spherical motion trajectory prediction points is basically blank. Based on this, this study is based on deep learning technology, and obtains the main experimental data through network data collection in the research and builds the table tennis spatial position image data set under various environments with accurate annotation based on the traditional deep learning. At the same time, the convolutional neural network is used as the …location recognition algorithm, and a prediction algorithm for predicting the trajectory of table tennis is proposed based on the recurrent neural network. In addition, this paper designs comparative experiments to analyze the effectiveness of the algorithm model, and evaluates the real-time recognition, location and trajectory prediction capabilities, and conducts quantitative analysis. The research shows that the algorithm has certain practical effects and can provide theoretical reference for subsequent related research. Show more

Keywords: Deep learning, neural network, trajectory, recognition algorithm, prediction model

DOI: 10.3233/JIFS-179209

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6275-6285, 2019