摘要
以世界优秀男子乒乓球运动员的比赛数据为训练样本,利用人工神经网络强大的自学习功能建立了乒乓球比赛获胜的诊断模型。根据乒乓球比赛的主要技战术指标数据,利用该模型能较好地诊断比赛的获胜概率,诊断精度较高。同时运用该模型计算了影响乒乓球比赛获胜的主要技战术指标的权重值,为有针对性的指导运动员训练提供了科学参考。
Taking the competition data of the world elite men＇s table tennis players as the training sample, the authors used the strong self-learning function of artificial neural network to establish a diagnostic model of table tennis competition. By using the main technical and tactical data in competition, the model may give the probability of winning and the precision of the diagnosis is quite high. The paper uses the model to calculate the weight values of the main indicators that affects the winning of the table tennis games so as to provide scientific reference for coaching the training of the players.
出处
《体育科研》
CSSCI
2008年第6期19-22,共4页
Sport Science Research
基金
2008国家体育总局奥运科研攻关与科技服务项目(07052)
关键词
神经网络
乒乓球
技战术
诊断模型
neural network
table tennis
technique and tactics
diagnostic model
