最优乒乓球运动员身体特征寻优筛选挖掘建模  

Modeling of Optimization Screening Mining for Optimal Table Tennis Athletes Physical Characteristics

作　　者：马媛媛[1] 杨磊[1] 

机构地区：[1]河南师范大学计算机与信息工程学院,河南新乡453007

出　　处：《计算机仿真》2015年第6期382-385,共4页Computer Simulation

摘　　要：根据运动训练学"项群训练理论",乒乓球项目属于技能主导类隔网对抗性项群,由于反映在运动员身体素质上具有显著性差异的身体形态指标和克托莱指数的相关参数很难准确提取,传统的迭代优化筛选方法对于一些复杂和多参数情况进行最优身体特征参数估计处理时,性能上会造成极大的瓶颈。提出一种利用遗传算法对乒乓球运动员身体特征逐步寻优的挖掘模型。通过上述模型从乒乓球运动员身体特征空间中挖掘出多个未知特征,并以树状的层次方式逐步分离,对乒乓球运动员身体特征进行符号化处理,提出了基于知识的空间特征逐步寻优挖掘模型。仿真结果证明,上述挖掘模型应用于运动员寻优筛选中,提高了筛选效率,并且对一定范围内的不同取样的筛选具有一定的稳定性。According to sports training ＂XiangQun training theory＂, table tennis project belongs to the dominant class skills netting item - group. Because the physical qualities of athletes have significant difference, the related pa- rameters of body shape index and body mass index are very difficult to accurately extracted. There is great bottleneck in traditional iterative optimization screening method for some complex and multiple parameters for optimal physical characteristic parameters estimation. An optimization mining model of physical features for table tennis athletes is presented by using the genetic algorithm. Unknown characteristics are mined from the body feature space of table ten- nis athletes by the model, and they are gradually separated and symbolically processed. Then a gradually optimization method of spatial characteristics is presented based on the knowledge. Simulation results show that the proposed min- ing model can improve the screening efficiency and to a certain range of different sample, the screening has certain stability.

关 键 词：逐步寻优 身体特征 遗传算法 

分 类 号：TP22[自动化与计算机技术—检测技术与自动化装置]