Sports Training System Based on Convolutional Neural Networks and Data Mining.

Yuwang Zhang,Yuan Zhang

doi:10.1155/2021/1331759

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%.

Highlights

There are some problems in the daily training process, such as single training method long-term training leading to bone and joint injury
In order to improve the training efficiency of athletes in the daily training process and make full use of the data information in the training process, Hassib et al chose a convolutional neural network algorithm to analyze the data of two groups of different teams in the competition. is study confirmed the effectiveness of this method in guiding athletes during basketball games [9]
Through the deep learning of individual characteristics, gait tracking, and training environment among athletes, the construction of training gait recognition model based on convolutional neural network algorithm is realized

Summary

Introduction

There are some problems in the daily training process, such as single training method long-term training leading to bone and joint injury. [1]. Computational Intelligence and Neuroscience affecting sports training with the athlete’s gait recognition process, combined with neural network algorithms, to study the influence of gait recognition on sports performance [11]. Aiming at the problem of “only simple migration and application of intelligent algorithms, but not deep mining of the value of data” existing in the latest research, research on sports training systems based on convolutional neural networks and data mining has important practical significance. Through the deep learning of individual characteristics, gait tracking, and training environment among athletes, the construction of training gait recognition model based on convolutional neural network algorithm is realized. The multilayer convolutional neural network algorithm structure is used in the sports training system for a certain sports event and the training information intelligent processing model based on existing athletes.

Sports Training System Based on Convolutional Neural Network and Data Mining

Analysis and Discussion

87.5 Experimental group 1-1 data set Experimental group

Conclusion