Sports Competition Stressors Based On K-Means Algorithm

Ranjit Kumar (), Zhengwu Liu and Wan Zamri
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Ranjit Kumar: Institute of Sports Science & Technology, Pune, India
Zhengwu Liu: Weinan Normal University, China
Wan Zamri: Faculty of Applied Sciences, Tunku Abdul Rahman University College, Setapak, Kuala Lumpur, Malaysia

Malaysian Sports Journal (MSJ), 2019, vol. 1, issue 1, 04-07

Abstract: In view of the data characteristics of the sports competition stressor, a new improved hierarchical K-Means algorithm is formed by combining the known partition algorithm K-Means algorithm with the hierarchical algorithm. At the same time, the improved algorithm is really applied to the data of sports competition stressor, and the clustering results are obtained and analyzed. The results show that different types of athletes face different pressures due to their own conditions and external environment, and their stressors are quite different. It is concluded that for different types of players, their own circumstances should be considered. It is necessary to conduct emotional guidance to prevent the negative emotion of the athletes.

Keywords: K-Means algorithm; stressors; sports competition; clustering (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:zib:zbnmsj:v:1:y:2019:i:1:p:04-07

DOI: 10.26480/msj.01.2019.04.07

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