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基于突变模糊神经网络的运动损伤估计模型分析。

Analysis of Sports Injury Estimation Model Based on Mutation Fuzzy Neural Network.

机构信息

College of Sports Rehabilitation, Shanxi Medical University, Taiyuan, Shanxi 030001, China.

Graduate Institute of Sport Coaching Science, College of Kinesiology and Health, Chinese Culture University, 55, Hwa-Kang Rd, Yang-Mung-Shan, Taipei, Taiwan 11114, China.

出版信息

Comput Intell Neurosci. 2021 Dec 1;2021:3056428. doi: 10.1155/2021/3056428. eCollection 2021.

DOI:10.1155/2021/3056428
PMID:34899890
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8654572/
Abstract

In recent years, with the gradual development of sports, the competition between athletes is becoming more and more fierce. The long training time and heavy body load of athletes lead to the increase of the incidence of sports injury, and the evaluation and analysis of athletes' sports injury need a lot of manpower and material resources. In order to improve the calculation efficiency of sports injury estimation results and save the cost of estimation and analysis, we propose a sports injury estimation model based on the algorithm model of mutation fuzzy neural network. The sports injury model constructed in this paper can not only systematically evaluate and analyze the degree of sports injury of athletes, but also improve the accuracy and efficiency; at the same time, it has universality for the evaluation and analysis of the degree of sports injury. The construction of this model provides the theoretical basis of big data algorithm for the prevention of sports injury and the application of mutation fuzzy neural network in the field of sports.

摘要

近年来，随着体育事业的逐渐发展，运动员之间的竞争也越来越激烈。运动员长时间的训练以及较大的身体负荷导致运动损伤的发生率不断提高，对运动员运动损伤的评估和分析需要耗费大量的人力和物力。为了提高运动损伤预估结果的计算效率，节约预估分析的成本，提出了一种基于突变模糊神经网络算法模型的运动损伤预估模型。本文构建的运动损伤模型不仅可以系统地评估和分析运动员运动损伤的程度，还可以提高预估的准确性和效率；同时，对运动员运动损伤程度的评估分析具有通用性。该模型的构建为运动损伤的预防提供了大数据算法的理论基础，也为突变模糊神经网络在体育领域的应用提供了理论依据。

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