混沌理论和机器学习算法的运动员成绩预测模型  

Athletes performance prediction model based on chaos theory and machine learning algorithm

作　　者：高素霞 GAO Suxia(Henan Institute of Technology,Xinxiang 450044,China)

机构地区：[1]河南工学院,河南新乡450044

出　　处：《现代电子技术》2018年第7期152-155,共4页Modern Electronics Technique

摘　　要：为了准确地对运动员成绩进行预测,结合运动员成绩的具体变化特点,设计了基于混沌理论和机器学习算法的运动员成绩预测模型。首先对当前运动员成绩建模与预测的研究现状进行分析,找到当前运动员成绩预测模型存在的不足,然后采用混沌理论对运动员成绩历史数据进行处理,发现其中隐藏的规律,最后引入机器学习算法——极限学习机设计运动员成绩预测模型。仿真实验结果表明,与当前运动员成绩预测模型相比,所设计模型的运动员成绩预测结果更加可靠,而且运动员成绩预测精度更高,可以应用于体育科学训练计划制定。In order to predict the athletes performance accurately,the specific change characteristics of athletes perfor-mance is combined to design the athletes performance prediction model based on chaos theory and machine learning algorithm.The current research status of athletes performance modeling and prediction is analyzed to find the shortcomings of the current athletics performance prediction models.The chaos theory is used to process the athletes′historical data,and find its hidden rules.The machine learning algorithm(extreme learning machine)is introduced to design the athletes performance prediction model.The simulation and experiment results show that,in comparison with the current athletics performance prediction models,the prediction model has more reliable athletes performance prediction result and higher prediction accuracy,and can be ap-plied to the plan formulation of sports scientific training.

关 键 词：运动员成绩 机器学习算法 混沌理论 原始数据 成绩预测模型 极限学习机 

分 类 号：TN911.1-34[电子电信—通信与信息系统] TP391[电子电信—信息与通信工程]