{"title":"The application of deep learning in college students’ sports cognition and health concept","authors":"Ping Wang, Xiaopeng Chi, Yue-Xun Yu","doi":"10.3233/JIFS-219014","DOIUrl":null,"url":null,"abstract":"Researchers and scientists in practical sports psychology are involved in the sports psychology practice process. Current models of training appear unsatisfied to assist trainees in psychology to learn the necessary humanistic skills for the requirement of athlete-centered services. This article aims to include an example of the value of Deep Neural Network Assisted Reflective Approaches (DNARA) as an alternative to clinical training, which may enable practitioners to manage themselves better in action. It addresses the essence of professional understanding; To describe reflection and present common examples of a reflective method in the “education professions” during the creation of reflective practice. It discusses how reflective exercise can support a clinician’s professional and personal growth within the field of sport psychology and illustrate how reflective practice may improve. Finally, there is a discussion about appropriate platforms for the distribution of insightful content. DNARA method achieves the highest classification accuracy of 94.12%, and error rate is reduced to 0.40, and DNARA method is more efficient for student health concepts.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2021-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Fuzzy Logic and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/JIFS-219014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 3
Abstract
Researchers and scientists in practical sports psychology are involved in the sports psychology practice process. Current models of training appear unsatisfied to assist trainees in psychology to learn the necessary humanistic skills for the requirement of athlete-centered services. This article aims to include an example of the value of Deep Neural Network Assisted Reflective Approaches (DNARA) as an alternative to clinical training, which may enable practitioners to manage themselves better in action. It addresses the essence of professional understanding; To describe reflection and present common examples of a reflective method in the “education professions” during the creation of reflective practice. It discusses how reflective exercise can support a clinician’s professional and personal growth within the field of sport psychology and illustrate how reflective practice may improve. Finally, there is a discussion about appropriate platforms for the distribution of insightful content. DNARA method achieves the highest classification accuracy of 94.12%, and error rate is reduced to 0.40, and DNARA method is more efficient for student health concepts.
期刊介绍:
The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.