Research on Athlete Training Effect Evaluation Based on Machine Learning Algorithm

被引:0
|
作者
Zou, Yan [1 ]
Wang, Chu [2 ]
Jiao, Qianqian [1 ]
机构
[1] Wenzhou Med Univ, Higher Educ Pk, Wenzhou 325015, Zhejiang, Peoples R China
[2] Kogi Univ, 79 Gamasil Gil Hayang Eup, Gyongsan 38428, South Korea
关键词
POSE ESTIMATION; VIDEO;
D O I
10.1155/2022/3707879
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In order to achieve a quantitative analysis of the training effects of athletes, this paper combines machine learning algorithms to evaluate and analyze athletes' training effects and analyzes the evaluation algorithms based on machine learning interpretable models. Moreover, after analyzing a variety of algorithms, this paper selects an intelligent evaluation method suitable for this model and builds an intelligent evaluation system based on the current athletes' training needs. In addition, this paper verifies the effect of the system with the support of intelligent algorithms and experiments. The experimental research results show that the athlete training effect evaluation system based on the machine learning algorithm proposed in this paper has good results, and it can be applied to subsequent athletes' sports training evaluation.
引用
收藏
页数:10
相关论文
共 50 条