In the non-medical model physiological parameter monitoring system, learning the monitoring parameters can improve the diagnostic and prediction accuracy. Aiming at the problems of insufficient information mining and low prediction accuracy in multi-task time series, the supervised and semi-supervised learning methods in machine learning are combined to predict the physiological status of remote health monitoring objects. This method uses the K-means algorithm to cluster the same type of data and use the Multitasking Least Squares Support Vector Machine (MTLS-SVM) to train historical data for trend prediction. In order to evaluate the effectiveness of the method, the MTLS-SVM method is compared with the K-means and MTLS-SVM methods. It can be seen from the experimental results that the body temperature data measured by the GY-MCU90615 is close to that of the digital thermometer. Moreover, the body temperature speed collected by the GY-MCU90615 can reach the millisecond level, which can well meet the needs of the system. The research shows that the method has higher prediction accuracy and has a breakthrough significance for the monitoring of athletes’ physiological parameters.
{"title":"Athlete’s physiological parameter monitoring system based on K-means and MTLS-SVM algorithm","authors":"Yang Wu","doi":"10.3233/JIFS-189915","DOIUrl":"https://doi.org/10.3233/JIFS-189915","url":null,"abstract":"In the non-medical model physiological parameter monitoring system, learning the monitoring parameters can improve the diagnostic and prediction accuracy. Aiming at the problems of insufficient information mining and low prediction accuracy in multi-task time series, the supervised and semi-supervised learning methods in machine learning are combined to predict the physiological status of remote health monitoring objects. This method uses the K-means algorithm to cluster the same type of data and use the Multitasking Least Squares Support Vector Machine (MTLS-SVM) to train historical data for trend prediction. In order to evaluate the effectiveness of the method, the MTLS-SVM method is compared with the K-means and MTLS-SVM methods. It can be seen from the experimental results that the body temperature data measured by the GY-MCU90615 is close to that of the digital thermometer. Moreover, the body temperature speed collected by the GY-MCU90615 can reach the millisecond level, which can well meet the needs of the system. The research shows that the method has higher prediction accuracy and has a breakthrough significance for the monitoring of athletes’ physiological parameters.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"9 1","pages":"1-9"},"PeriodicalIF":1.3,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82145385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the development of globalization, people’s demand for English audio interaction is increasing. In order to overcome the shortcomings of traditional translation methods in grammatical variables, such as semantic ambiguity, quantifier errors, low translation accuracy, improve the quality and speed of English translation, and get more accurate and speed guaranteed translation, this study proposes an artificial intelligence English audio translation cross language system based on fuzzy algorithm. In this experiment, the collected analog speech signal is converted into a digital speech signal, and then, the speech features are modeled and digitized, and the whole set of speech samples are integrated and modified to eliminate the interference caused by noise as far as possible. After that, the collected voice will be stored in the text format, and then the text will be translated to achieve English audio translation. The DNN-HMM speech recognition model and the traditional GMM-HMM speech recognition model are used to preprocess the original corpus, and the accuracy of the corpus processing is compared. After that, the accuracy and utilization of the fuzzy algorithm are evaluated between the first type TSK and the second type TSK. For speech synthesis in which the corpus lacks language, it is meaningful to explore the least amount of training data for the synthesis of acceptable speech. The experimental results show that the accuracy of the fuzzy algorithm is about 97.34%, and the utilization rate is about 98.14%. The accuracy rate of type 1 and type 2 algorithms are about 85.77% and 76.87% respectively, and the utilization rate is about 83.25% and 78.63% respectively. The fuzzy algorithm based artificial intelligence English audio translation cross language system is obviously better than the other two algorithms.
{"title":"Application research of artificial intelligence English audio translation system based on fuzzy algorithm","authors":"Erying Guo","doi":"10.3233/JIFS-189829","DOIUrl":"https://doi.org/10.3233/JIFS-189829","url":null,"abstract":"With the development of globalization, people’s demand for English audio interaction is increasing. In order to overcome the shortcomings of traditional translation methods in grammatical variables, such as semantic ambiguity, quantifier errors, low translation accuracy, improve the quality and speed of English translation, and get more accurate and speed guaranteed translation, this study proposes an artificial intelligence English audio translation cross language system based on fuzzy algorithm. In this experiment, the collected analog speech signal is converted into a digital speech signal, and then, the speech features are modeled and digitized, and the whole set of speech samples are integrated and modified to eliminate the interference caused by noise as far as possible. After that, the collected voice will be stored in the text format, and then the text will be translated to achieve English audio translation. The DNN-HMM speech recognition model and the traditional GMM-HMM speech recognition model are used to preprocess the original corpus, and the accuracy of the corpus processing is compared. After that, the accuracy and utilization of the fuzzy algorithm are evaluated between the first type TSK and the second type TSK. For speech synthesis in which the corpus lacks language, it is meaningful to explore the least amount of training data for the synthesis of acceptable speech. The experimental results show that the accuracy of the fuzzy algorithm is about 97.34%, and the utilization rate is about 98.14%. The accuracy rate of type 1 and type 2 algorithms are about 85.77% and 76.87% respectively, and the utilization rate is about 83.25% and 78.63% respectively. The fuzzy algorithm based artificial intelligence English audio translation cross language system is obviously better than the other two algorithms.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"1 1","pages":"1-10"},"PeriodicalIF":1.3,"publicationDate":"2021-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75574966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the improvement of software system complexity and frequent updating of user requirements, the requirements of the information software development industry for information construction are constantly improved, and the quality and management requirements of software products researched and developed are also constantly improved. Project managers in the information software development industry gradually realize the importance and necessity of software system deployment. It requires scientific, timely, effective and clear work. Software system deployment system for task division and task monitoring. Based on the research results at home and abroad, this paper studies the deployment of computer software system based on event-driven architecture by using a discrete Fourier transform algorithm, decision tree algorithm and parallel algorithm. By comparing and optimizing the advantages and disadvantages of discrete Fourier transform algorithm, decision tree algorithm and parallel algorithm. This paper studies the unified management, scheduling and allocation of computer software resources. The results show that after using the research model, the data error is controlled within 5%, and the overall data accuracy is improved by 15% compared with the previous methods, which have certain practical value.
{"title":"Allocation and application of computer software system based on system architecture","authors":"Xiao Di","doi":"10.3233/JIFS-189841","DOIUrl":"https://doi.org/10.3233/JIFS-189841","url":null,"abstract":" With the improvement of software system complexity and frequent updating of user requirements, the requirements of the information software development industry for information construction are constantly improved, and the quality and management requirements of software products researched and developed are also constantly improved. Project managers in the information software development industry gradually realize the importance and necessity of software system deployment. It requires scientific, timely, effective and clear work. Software system deployment system for task division and task monitoring. Based on the research results at home and abroad, this paper studies the deployment of computer software system based on event-driven architecture by using a discrete Fourier transform algorithm, decision tree algorithm and parallel algorithm. By comparing and optimizing the advantages and disadvantages of discrete Fourier transform algorithm, decision tree algorithm and parallel algorithm. This paper studies the unified management, scheduling and allocation of computer software resources. The results show that after using the research model, the data error is controlled within 5%, and the overall data accuracy is improved by 15% compared with the previous methods, which have certain practical value.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"15 1","pages":"1-8"},"PeriodicalIF":1.3,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79050938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The underlying concept of the Internet of Things 7 (IoT), several studies IoT will dramatically change 8 our daily life. It can be imagined that the era of the 9 Internet of Intelligent Systems will be coming to us 10 soon. The development of IoT, however, has reached 11 a crossroads. Without intelligence, IoT systems will 12 act as an ordinary information system the reactions 13 of which are based on a set of predefined rules. They 14 may not be the services we are looking for. Besides, 15 there is a growing awareness that the complexity of 16 managing Intelligent Systems Big Data is one of the 17 main challenges in the developing field of the Inter18 net of Things (IoT). Complexity arises from several 19 aspects of the Big Data life cycle, such as gather20 ing data, storing them onto cloud servers. Among 21 the intelligent technologies, how to handle the mas22 sive amount of data generated by the systems and 23 devices of the IoT has been widely considered. Many 24 technologies, such as data mining, big data analytics, 25 statistical and other analysis technologies, have also
{"title":"Adaptive internet of things and machine learning techniques for managing the complexity of intelligent systems big data","authors":"Ahmed A. Elngar","doi":"10.3233/JIFS-189844","DOIUrl":"https://doi.org/10.3233/JIFS-189844","url":null,"abstract":"The underlying concept of the Internet of Things 7 (IoT), several studies IoT will dramatically change 8 our daily life. It can be imagined that the era of the 9 Internet of Intelligent Systems will be coming to us 10 soon. The development of IoT, however, has reached 11 a crossroads. Without intelligence, IoT systems will 12 act as an ordinary information system the reactions 13 of which are based on a set of predefined rules. They 14 may not be the services we are looking for. Besides, 15 there is a growing awareness that the complexity of 16 managing Intelligent Systems Big Data is one of the 17 main challenges in the developing field of the Inter18 net of Things (IoT). Complexity arises from several 19 aspects of the Big Data life cycle, such as gather20 ing data, storing them onto cloud servers. Among 21 the intelligent technologies, how to handle the mas22 sive amount of data generated by the systems and 23 devices of the IoT has been widely considered. Many 24 technologies, such as data mining, big data analytics, 25 statistical and other analysis technologies, have also","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"35 1","pages":"1-1"},"PeriodicalIF":1.3,"publicationDate":"2021-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79575241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The importance of the management of ideological and political theory courses in colleges and universities is objective to the importance of ideological and political theory courses. At present, the management of ideological and political theory courses in colleges and universities has big problems in both macro and micro aspects. This paper combines artificial intelligence technology to build an intelligent management system for ideological and political education in colleges and universities based on artificial intelligence, and conducts classroom supervision through intelligent recognition of student status. The KNN outlier detection algorithm based on KD-Tree is proposed to extract the state information of class students. Through data simulation, it can be known that the KD-KNN outlier detection algorithm proposed in this paper significantly improves the efficiency of the algorithm while ensuring the accuracy of the KNN algorithm classification. Through experimental research, it can be seen that the construction of this system not only clarifies the direction of management from a macro perspective, but also reveals specific methods of management from a micro perspective, and to a certain extent effectively solves the problems in the management of ideological and political theory courses in colleges and universities.
{"title":"Research on the framework of university ideological and political education management system based on artificial intelligence","authors":"Xu Sun, Yu Zhang","doi":"10.3233/JIFS-219134","DOIUrl":"https://doi.org/10.3233/JIFS-219134","url":null,"abstract":"The importance of the management of ideological and political theory courses in colleges and universities is objective to the importance of ideological and political theory courses. At present, the management of ideological and political theory courses in colleges and universities has big problems in both macro and micro aspects. This paper combines artificial intelligence technology to build an intelligent management system for ideological and political education in colleges and universities based on artificial intelligence, and conducts classroom supervision through intelligent recognition of student status. The KNN outlier detection algorithm based on KD-Tree is proposed to extract the state information of class students. Through data simulation, it can be known that the KD-KNN outlier detection algorithm proposed in this paper significantly improves the efficiency of the algorithm while ensuring the accuracy of the KNN algorithm classification. Through experimental research, it can be seen that the construction of this system not only clarifies the direction of management from a macro perspective, but also reveals specific methods of management from a micro perspective, and to a certain extent effectively solves the problems in the management of ideological and political theory courses in colleges and universities.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"6 1","pages":"1-10"},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73606242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, China’s colleges have made gratifying achievements in the funding work of poor students, but there are still some problems. In order to improve the accuracy of the funding work, the performance of the poor students in colleges should be evaluated effectively. This paper uses the design idea based on the whole process, and the fuzzy comprehensive evaluation method and the hierarchical analysis method, and constructs the performance evaluation index system of the poor students in colleges. Then, taking the performance evaluation of poor students’ support in Jiangxi University of Technology as an example, according to China’s national conditions, the empirical analysis shows that the poverty students’ support work in Jiangxi University of Technology is at the general level, and can be improved from four aspects: perfecting the mechanism of identifying poor students, broadening the funding channels, perfecting the supervision mechanism of financial aid for poor students, and combining financial aid with mental support. The research of this paper is of great significance to improve the management level of the funding of poor students in colleges and universities.
{"title":"The evaluation of the performance of the poor students in colleges based on the fuzzy comprehensive evaluation method","authors":"L. Qiu, Wenbin Yang, Ting Wang","doi":"10.3233/JIFS-219029","DOIUrl":"https://doi.org/10.3233/JIFS-219029","url":null,"abstract":"In recent years, China’s colleges have made gratifying achievements in the funding work of poor students, but there are still some problems. In order to improve the accuracy of the funding work, the performance of the poor students in colleges should be evaluated effectively. This paper uses the design idea based on the whole process, and the fuzzy comprehensive evaluation method and the hierarchical analysis method, and constructs the performance evaluation index system of the poor students in colleges. Then, taking the performance evaluation of poor students’ support in Jiangxi University of Technology as an example, according to China’s national conditions, the empirical analysis shows that the poverty students’ support work in Jiangxi University of Technology is at the general level, and can be improved from four aspects: perfecting the mechanism of identifying poor students, broadening the funding channels, perfecting the supervision mechanism of financial aid for poor students, and combining financial aid with mental support. The research of this paper is of great significance to improve the management level of the funding of poor students in colleges and universities.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"108 ","pages":"1-11"},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JIFS-219029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72422594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Jin, Xiaojuan Su, Yeqing Wang, Dai Shi, Liang Xu
Traditional brain imaging usually does not show anomalies. Based on this, this study used DTI to find evidence that the brain structure microstructure may be abnormal, and to study the BOLD signal changes of functional magnetic resonance imaging and the changes of DTI microstructure in patients with mild traumatic brain injury. At the same time, based on literature collection and actual data, the current status of nuclear magnetic resonance diagnosis of brain trauma was collected. Moreover, this study combines the problem to improve the algorithm and propose an image diagnosis method for brain trauma to improve the cluster quality and stability. In addition, the experiment was designed to analyze the performance of the algorithm in this study. Finally, in this study, resting state functional magnetic resonance imaging was used to study the resting brain function in patients with mild cognitive impairment within one week after traumatic brain injury. The results show that the method proposed in this study has certain effects and can provide theoretical reference for related research.
{"title":"Intelligent diagnostic analysis based on pattern recognition of DTI image","authors":"D. Jin, Xiaojuan Su, Yeqing Wang, Dai Shi, Liang Xu","doi":"10.3233/JIFS-189797","DOIUrl":"https://doi.org/10.3233/JIFS-189797","url":null,"abstract":"Traditional brain imaging usually does not show anomalies. Based on this, this study used DTI to find evidence that the brain structure microstructure may be abnormal, and to study the BOLD signal changes of functional magnetic resonance imaging and the changes of DTI microstructure in patients with mild traumatic brain injury. At the same time, based on literature collection and actual data, the current status of nuclear magnetic resonance diagnosis of brain trauma was collected. Moreover, this study combines the problem to improve the algorithm and propose an image diagnosis method for brain trauma to improve the cluster quality and stability. In addition, the experiment was designed to analyze the performance of the algorithm in this study. Finally, in this study, resting state functional magnetic resonance imaging was used to study the resting brain function in patients with mild cognitive impairment within one week after traumatic brain injury. The results show that the method proposed in this study has certain effects and can provide theoretical reference for related research.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"163 1","pages":"1-11"},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80279278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the advent of the information age, computer-related application research has become more and more extensive, human motion analysis and action scoring based on computer vision have gradually become the focus of attention. In order to adapt to the development of the times and solve the problems related to the analysis of human motion, the experiment analyzed the similarity of eight common human movement behaviors, analyze the movement speed of men and women under sports training, and analyzed the accuracy of the human body motion recognition model in the two cases of the original gray data and the frame difference channel, finally, the denoising performance of four different algorithms of SMF, EMF, RAMF and median filter algorithm in digital image processing is analyzed. The final result shows that there is a big similarity between the same kind of human movement behavior, the accuracy rate of the frame difference channel human body recognition model is higher than that of the original gray data recognition model, and digital image processing median filter algorithm has good image denoising performance.
{"title":"Human motion analysis and action scoring technology for sports training based on computer vision features","authors":"Yongheng Bai, Yinggang Chen","doi":"10.3233/JIFS-219092","DOIUrl":"https://doi.org/10.3233/JIFS-219092","url":null,"abstract":"With the advent of the information age, computer-related application research has become more and more extensive, human motion analysis and action scoring based on computer vision have gradually become the focus of attention. In order to adapt to the development of the times and solve the problems related to the analysis of human motion, the experiment analyzed the similarity of eight common human movement behaviors, analyze the movement speed of men and women under sports training, and analyzed the accuracy of the human body motion recognition model in the two cases of the original gray data and the frame difference channel, finally, the denoising performance of four different algorithms of SMF, EMF, RAMF and median filter algorithm in digital image processing is analyzed. The final result shows that there is a big similarity between the same kind of human movement behavior, the accuracy rate of the frame difference channel human body recognition model is higher than that of the original gray data recognition model, and digital image processing median filter algorithm has good image denoising performance.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"8 1","pages":"1-9"},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78886361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, the field of computer vision is promoted by the development of intelligent technology and computer technology, and has made breakthrough progress. Intelligent hardware technology and computer technology lay the foundation for the development of computer vision field. At the same time, the continuous improvement and development of artificial intelligence technology has also promoted the rapid development of educational video system, and the video tracking of educational video system has made breakthrough progress. By fully using intelligent hardware and computer technology, and combining with artificial intelligence technology, the video tracking and recognition technology of educational video system has been further developed, and new recognition algorithm has been adopted. The accuracy of tracking recognition is greatly improved, which can accurately identify the action of the characters. At the same time, through the use of new action recognition algorithm, not only improve the accuracy of educational video recognition, but also improve the speed of recognition, which can accurately capture the changes of people’s behavior in the classroom. The time consumed by the action recognition algorithm is very short, and the speed of the algorithm is very high. This new algorithm greatly improves the efficiency of the education recording and broadcasting system, and improves the accuracy and accuracy of the education recording and broadcasting system. This paper studies a set of intelligent image recognition system for students’ classroom behavior. It compiles and explains the intelligent system software systematically. The operation of this system is no single. It operates through the joint operation of many modules. It can realize online distributed homework, accurately and quickly identify students’ classroom behavior, and can also help students to identify their classroom behavior accurately and quickly. The classroom behavior of the accurate analysis of students’ incorrect classroom behavior to make timely reminders, greatly improve the efficiency of the classroom, improve the degree of concentration of students. In this paper, many classroom behaviors are simulated, and the performance of this software platform is predicted through many experiments.
{"title":"Remote classroom action recognition based on improved neural network and face recognition","authors":"L. Mao","doi":"10.3233/JIFS-189803","DOIUrl":"https://doi.org/10.3233/JIFS-189803","url":null,"abstract":"In recent years, the field of computer vision is promoted by the development of intelligent technology and computer technology, and has made breakthrough progress. Intelligent hardware technology and computer technology lay the foundation for the development of computer vision field. At the same time, the continuous improvement and development of artificial intelligence technology has also promoted the rapid development of educational video system, and the video tracking of educational video system has made breakthrough progress. By fully using intelligent hardware and computer technology, and combining with artificial intelligence technology, the video tracking and recognition technology of educational video system has been further developed, and new recognition algorithm has been adopted. The accuracy of tracking recognition is greatly improved, which can accurately identify the action of the characters. At the same time, through the use of new action recognition algorithm, not only improve the accuracy of educational video recognition, but also improve the speed of recognition, which can accurately capture the changes of people’s behavior in the classroom. The time consumed by the action recognition algorithm is very short, and the speed of the algorithm is very high. This new algorithm greatly improves the efficiency of the education recording and broadcasting system, and improves the accuracy and accuracy of the education recording and broadcasting system. This paper studies a set of intelligent image recognition system for students’ classroom behavior. It compiles and explains the intelligent system software systematically. The operation of this system is no single. It operates through the joint operation of many modules. It can realize online distributed homework, accurately and quickly identify students’ classroom behavior, and can also help students to identify their classroom behavior accurately and quickly. The classroom behavior of the accurate analysis of students’ incorrect classroom behavior to make timely reminders, greatly improve the efficiency of the classroom, improve the degree of concentration of students. In this paper, many classroom behaviors are simulated, and the performance of this software platform is predicted through many experiments.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"360 1","pages":"1-11"},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76463126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As the world’s largest free trade area among developing countries, the China-ASEAN Free Trade Area has gone through 15 years, and the China-ASEAN (Association of Southeast Asian Nations) Free Trade Area cooperation framework with tariff reduction as the core has diminished incentive effects on regional trade, the “21st Century Maritime Silk Road” strategy provide new opportunities for the upgrading and development of the China-ASEAN Free Trade Area. Based on the stochastic frontier gravity model, the random disturbance term was introduced to overcome the inevitable noise problem of macro statistical data, the trade efficiency of agricultural products between China and ASEAN were estimated in this study. The result shows that the potential for trade promotion between China and ASEAN countries is fully tapped. Based on this, it is proposed to strengthen infrastructure construction and smooth maritime trade channels with the help of the “One Road” platform. Strengthen communication and dialogue to weaken the impact of non-tariff barriers on trade, and use the Shanghai Free Trade Zone test plot to enhance the international competitiveness of Chinese agricultural product trade.
{"title":"Intelligent evaluation of trade efficiency of agricultural products between China and ASEAN: An stochastic frontier approach with noise reduction","authors":"Shuaiwen Wang","doi":"10.3233/JIFS-189928","DOIUrl":"https://doi.org/10.3233/JIFS-189928","url":null,"abstract":"As the world’s largest free trade area among developing countries, the China-ASEAN Free Trade Area has gone through 15 years, and the China-ASEAN (Association of Southeast Asian Nations) Free Trade Area cooperation framework with tariff reduction as the core has diminished incentive effects on regional trade, the “21st Century Maritime Silk Road” strategy provide new opportunities for the upgrading and development of the China-ASEAN Free Trade Area. Based on the stochastic frontier gravity model, the random disturbance term was introduced to overcome the inevitable noise problem of macro statistical data, the trade efficiency of agricultural products between China and ASEAN were estimated in this study. The result shows that the potential for trade promotion between China and ASEAN countries is fully tapped. Based on this, it is proposed to strengthen infrastructure construction and smooth maritime trade channels with the help of the “One Road” platform. Strengthen communication and dialogue to weaken the impact of non-tariff barriers on trade, and use the Shanghai Free Trade Zone test plot to enhance the international competitiveness of Chinese agricultural product trade.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"64 1","pages":"1-10"},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86197081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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