International Journal of Fuzzy Logic and Intelligent Systems最新文献

{"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":null,"pages":null},"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}

{"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":null,"pages":null},"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}

{"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":null,"pages":null},"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}

{"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":null,"pages":null},"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}

{"title":"Scene text spotting based on end-to-end","authors":"Guangcun Wei, Wansheng Rong, Yongquan Liang, Xinguang Xiao, Xiang Liu","doi":"10.3233/JIFS-200903","DOIUrl":"https://doi.org/10.3233/JIFS-200903","url":null,"abstract":"Aiming at the problem that the traditional OCR processing method ignores the inherent connection between the text detection task and the text recognition task, This paper propose a novel end-to-end text spotting framework. The framework includes three parts: shared convolutional feature network, text detector and text recognizer. By sharing convolutional feature network, the text detection network and the text recognition network can be jointly optimized at the same time. On the one hand, it can reduce the computational burden; on the other hand, it can effectively use the inherent connection between text detection and text recognition. This model add the TCM (Text Context Module) on the basis of Mask RCNN, which can effectively solve the negative sample problem in text detection tasks. This paper propose a text recognition model based on the SAM-BiLSTM (spatial attention mechanism with BiLSTM), which can more effectively extract the semantic information between characters. This model significantly surpasses state-of-the-art methods on a number of text detection and text spotting benchmarks, including ICDAR 2015, Total-Text.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75284427","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}

{"title":"Customer knowledge management competence evaluation of tourism enterprises based on ahp-fuzzy comprehensive evaluation method","authors":"Cheng Guoyi, Jiansheng Zhang, Zhang Shangmin, B. Yan","doi":"10.3233/JIFS-189902","DOIUrl":"https://doi.org/10.3233/JIFS-189902","url":null,"abstract":"With the fierce competition under the background of knowledge-based economy, tourism enterprises are increasingly aware that they must turn their focus from traditional products to customers for the sake of survival and development. Integrating the customer relationship management and knowledge management, the customer knowledge management (CKM) has aroused higher attention from the tourism enterprises. As for how to determine the factors influencing the Customer knowledge management competence (CKMC) of tourism enterprises and their weights, an index system was established for evaluating CKMC of tourism enterprises based on the balanced score card (BSC) and knowledge management process, the weight design and consistency check of the indexes were implemented using the analytic hierarchy process (AHP), and the overall evaluation value and concrete index scores at all levels were obtained via the fuzzy comprehensive evaluation model. In the end, the scientificity and operability of the evaluation model were verified through an empirical analysis of China Youth Travel Service (CYTS). The results show that: (1) The business process, customer communication, system support, and market performance are important level I indexes used to measure the CKMC; (2) The key Level II factors influencing the CKMC of enterprises include customer knowledge sharing mechanism, timeliness of customer communication, degree of importance attached by senior leadership, and customer acquisition rate; (3) The evaluation model based on AHP and fuzzy evaluation method can objectively describe the overall up-to-standard degree of enterprises’ CKMC, and clearly identify the strengths and weaknesses. This research shows that the combination of AHP and fuzzy evaluation-based method is capable of more scientific and complete evaluation of CKMC, compensates for the deficiencies of single evaluation model, and provides a new method for the effective improvement of enterprises’ CKMC.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75815131","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}

{"title":"Application of digital image processing technology in online education under COVID-19 epidemic","authors":"Baoxian Jia, Wunong Zhang","doi":"10.3233/JIFS-219045","DOIUrl":"https://doi.org/10.3233/JIFS-219045","url":null,"abstract":"In the current epidemic situation, appropriate learning resources are the prerequisite and basis for effective online education. Current online education, teacher teaching, and student learning lack a sense of immersion and participation. The reason is that the technology of online education is lagging. The thesis introduces augmented reality technology to enhance the immersion and interactivity of online education; introduces the technology based on Hadhoop to store image resources and improve the speed of reading image resources; the use of random forest algorithm for image recognition digital information Mining to recommend the most suitable online resources. Image processing technology can develop appropriate interactions and functions according to different scenarios to enhance the immersion and participation of online teaching, comprehensively improve the quality of teaching and learning, and provide technical support for the improvement of online learning.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75391148","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}

{"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":null,"pages":null},"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}

{"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":null,"pages":null},"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}

{"title":"Design and implementation of typical dynamic traffic scenes based on virtual reality technology","authors":"Zhan-jun Si, Xinhui Xie, Donghan Zhang","doi":"10.3233/JIFS-189914","DOIUrl":"https://doi.org/10.3233/JIFS-189914","url":null,"abstract":"It is of great significance to simulate dangerous traffic environment with vehicle driving simulator for reducing and preventing road traffic accidents. Firstly, a typical dynamic traffic scene was obtained and designed by using genetic algorithm, then a chaotic algorithm based on computer virtual reality scene was proposed. Finally, a dynamic scene in urban road scene was taken as an example, of which the simulation was designed and implemented by using virtual reality technology. The results show that the virtual operating environment of driver micro-traffic simulation can be effectively constructed with the combination of virtual reality technology and dynamic traffic scene.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78170023","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}