基于神经网络技术的运动损伤信息预测模型研究

Chunfeng Mao
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引用次数: 0

摘要

由于其强大的数据处理能力和数据挖掘能力,机器学习在各个研究领域得到了广泛的应用,并取得了突破。使用机器学习方法来研究运动损伤具有很大的潜力。BP神经网络技术是机器学习的重要内容之一。本文在神经网络基本模型的基础上,设计了BP神经网络的训练过程,构建了基于神经网络技术的运动损伤预测模型,包括神经网络的输入输出、层选择和参数选择,力求通过最少的迭代次数获得最佳的训练结果。研究结果可用于调整训练强度,增强运动员的自我保护意识,合理规划训练方法,避免运动损伤,保证运动训练的有效开展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Sports Injury Information Prediction Model Based on Neural Network Technology
Due to its powerful data processing capabilities and data mining capabilities, machine learning has been widely used in various fields of research and has achieved breakthroughs. The use of machine learning methods to study sports injuries has great potential. BP neural network technology is one of the important contents of machine learning. Based on the basic model of neural network, this paper designs the training process of BP neural network and builds the sports injury prediction model based on neural network technology, including the input and output of neural network, and the layer selection and parameter selection, and strive to get the best training results through the least number of iterations. The research results are used to adjust the training intensity, strengthen the athlete's self-protection awareness, rationally plan training methods, avoid sports injury, and ensure the effective development of sports training.
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