深度学习在大学生运动认知与健康观念中的应用

IF 1.5 Q2 COMPUTER SCIENCE, THEORY & METHODS International Journal of Fuzzy Logic and Intelligent Systems Pub Date : 2021-05-26 DOI:10.3233/JIFS-219014
Ping Wang, Xiaopeng Chi, Yue-Xun Yu
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引用次数: 3

摘要

实践运动心理学的研究人员和科学家参与到运动心理学的实践过程中。目前的训练模式似乎不满足于帮助心理学学员学习必要的人文技能,以满足以运动员为中心的服务要求。本文旨在包括深度神经网络辅助反思方法(DNARA)作为临床培训替代方案的价值示例,这可能使从业者在行动中更好地管理自己。它解决了专业理解的本质;描述反思,并提出反思方法在“教育专业”中创造反思实践的常见例子。它讨论了反思性练习如何在运动心理学领域支持临床医生的专业和个人成长,并说明了反思性练习如何改进。最后,本文讨论了传播有见地内容的合适平台。DNARA方法的分类准确率最高,达到94.12%,错误率降至0.40,DNARA方法对学生健康概念的分类效率更高。
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The application of deep learning in college students’ sports cognition and health concept
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.
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来源期刊
CiteScore
2.80
自引率
23.10%
发文量
31
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.
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