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Issue title: Fuzzy System for Economy Back on Track
Guest editors: Anand Paul, Simon K.S. Cheung, Chiung Ching Ho and Sadia Din
Article type: Research Article
Authors: Jinfeng, Liua; b | Bo, Yangc; *
Affiliations: [a] The Department of Physical Education, Huainan Normal University, Huainan, Anhui, China | [b] University of Perpetual Help System DALTA, Manila, Philippines | [c] Nanjing Medical University, Nanjing, Jiangsu, China
Correspondence: [*] Corresponding author. Yang Bo, Nanjing Medical University, China. liujftyjf@163.com
Abstract: The evaluation system of physical education is limited by many factors, so the reliability of the quantitative results of its intelligent scoring system is not high. In order to improve the teachingeffect ofphysical education major, this paper combines a machine learning algorithm and SVM to build anevaluation system of physical education. The system uses optimized machine learning as the system algorithm. In order to improve the operating efficiency of the system, this study optimizes the system physical layer certification to improve the system data processing speed and accuracy and uses a three-layer structure to build a basic model of the system structure and analyze its functional modules. Moreover, this study uses a database based on an expert evaluation system for data processing to achieve physical education evaluation and puts forward corresponding improvements. In addition, system performance verification is carried out on the basis of building the system. Through various experimental verifications, we know that the model constructed in this paper has good performance and can be applied to actual physical education.
Keywords: Machine learning, SVM, physical education, education evaluation, system construction
DOI: 10.3233/JIFS-189565
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7423-7434, 2021
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