Pressure source of athletes in field based on improved hierarchical K-means algorithm

Abstract

Nowadays, with the development of economy, sports industry attracts more and more people's attention, and the number and scale of sports events continue to expand. But the fierce competition, for athletes, is not only physical competition, psychological competition is particularly important. Psychological pressure is an important factor that affects athletes to play at a high level in the competition field. How to analyze the pressure source of athletes in the competition field is very important for athletes to overcome the competition pressure. Therefore, this paper designs a method based on the improved hierarchical K-Means clustering algorithm (KMCA) to analyze the pressure source of athletes in the competition field, so as to help athletes overcome the pressure on the competition field and promote their high-level performance. In this method, firstly, 182 athletes were investigated by questionnaire to obtain the data of related psychological pressure sources. Secondly, because KMCA is sensitive to the selection of initial class center, the performance of KMCA is directly related to the selection of initial class. Aiming at the problem of KMCA, this paper proposes an improved hierarchical KMCA. Finally, the improved hierarchical KMCA is applied to the clustering analysis of sports competition pressure source data. Through simulation analysis, compared with KMCA, the improved layered KMCA proposed in this paper has a good performance improvement. The improved hierarchical KMCA proposed in this paper can be applied to the analysis of the pressure source of athletes in the competition field, which can analyze the pressure of athletes and get the characteristics of the pressure of athletes, so as to help athletes overcome the pressure in the competition field and achieve the mental health of the competition field?