摘要
为了科学评价大学生身体素质,提出基于机器学习算法的体育成绩预测模型。对当前大学生体育成绩预测的研究现状进行分析,指出导致当前模型预测精度低的原因,采用机器学习算法——支持向量机建立大学生体育成绩预测模型,并采用粒子群算法选择模型参数,最后将该模型应用于某大学的体育成绩建模和预测中。应用实例结果表明,机器学习算法可以克服传统模型的不足,使得大学体育成绩预测效果得到改善,预测结果可以指导大学体育学科的改革。
In order to evaluate the physical quality of college students scientifically,a sports performance prediction modelbased on machine learning algorithm is put forward.The research status of the current college students sports performance prediction is analyzed to point out the reason causing the low prediction accuracy of current model.The machine learning algorithm(support vector machine)is used to establish the sports performance prediction model of college students.The particle swarmoptimization algorithm is adopted to choose the parameters of the model.The model is applied to the physical performancemodeling and prediction of a certain college.The application results show that the machine learning algorithm can eliminate theshortcomings of the traditional model,improve the prediction effect of the college sports performance,and its prediction resultscan guide the reformation of the college physical education.
作者
王晶
WANG Jing(Sias International University,Zhengzhou University,Xinzheng 451150,China)
出处
《现代电子技术》
北大核心
2017年第17期116-119,共4页
Modern Electronics Technique
关键词
体育训练
机器学习算法
预测模型
粒子群算法
physical training
machine learning algorithm
prediction model
particle swarm optimization algorithm
