摘要
为改善中国足球的竞技能力,提高运动员训练效果,提出基于数据挖掘技术的足球最优飞行轨迹估计方法。首先采用决策树方法对历史足球飞行轨迹数据构造树形架构,并在决策树上进行数据特征分类,提取足球飞行速度的大小、方向等分类结果,然后利用卡尔曼滤波估计足球飞行状态,通过时序解析和碰撞测试挖掘出足球最优飞行轨迹。实验结果表明,该方法估计结果与足球实际飞行轨迹的轨迹相似度高,可以应用于实际中。
In order to improve the competitive ability of Chinese football and training effect of athletes,a football optimalflight path estimation method based on data mining technology is proposed.The decision-making tree method is used to constructthe history football flight path data for the tree-form architecture.The data characteristics are classified on decision-making treeto extract the classification results such as the magnitude and direction of football flight speed.The Kalman filtering is adoptedto estimate the football flight state,by which the football optimal flight path is mined by means of temporal analysis and intersection test.The experimental results indicate that the estimation result of the proposed method has high path similarity with thepractical football flight path,and can be applied to the practical application.
作者
华正春
HUA Zhengchun(Guangxi Teachers Education University,Nanning 530023,China)
出处
《现代电子技术》
北大核心
2017年第19期123-125,128,共4页
Modern Electronics Technique
关键词
数据挖掘技术
最优飞行轨迹
决策树
卡尔曼滤波
data mining technology
optimal flight path
decision.making tree
Kalman filtering
作者简介
华正春（1985—），男，辽宁建平人，硕士，讲师。主要研究方向为体育学
