Sports Training System Based on Convolutional Neural Networks and Data Mining

Author:

Zhang Yuwang1ORCID,Zhang Yuan1

Affiliation:

1. Department of Physical Education, China University of Geosciences (Beijing), Beijing 100083, China

Abstract

In recent years, China’s sports industry has achieved good development, but the efficiency of athletes in the training process is difficult to have scientific guarantee. How to use scientific algorithm and data mining technology to accurately guide the sports training process has become a hot spot. Based on this, this paper studies the gait recognition model of sports training based on convolutional neural network algorithm. First, this paper analyzes the research status of gait recognition in the process of training and optimizes and improves the deficiencies in sports training. Then, the convolutional neural network algorithm and data mining technology are optimized and analyzed in the gait recognition model. Finally, the experimental results show that the convolutional neural network algorithm can realize the recognition and model reconstruction of athletes’ gait in the training process and can make the optimal strategy according to the gait differences of different athletes in the training process, and the recognition accuracy of athletes’ gait can reach more than 97%.

Publisher

Hindawi Limited

Subject

General Mathematics,General Medicine,General Neuroscience,General Computer Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Retracted: Sports Training System Based on Convolutional Neural Networks and Data Mining;Computational Intelligence and Neuroscience;2023-07-26

2. Research on the Application of Mobile Internet Information Technology in Sports Training System;Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023);2023

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