摘要
为了提高篮球运动员的选材预测水平,选取身体形态、运动素质、运动机能、技术水平等21项指标,形成篮球运动员选材的指标评价体系.采用灰色系统理论中的关联分析方法,对各个选材指标进行关联度分析,挑选出影响篮球运动员运动能力的核心选材因子.基于机器学习理论,以核心选材因子作为输入向量,以专家评定的运动能力作为输出向量,建立篮球运动员运动能力与核心选材因子之间的BP神经网络预测模型,通过网络持续训练与学习,找到核心选材因子与运动能力的内在关系.实验结果表明,提出的基于BP神经系统与灰色度模型的篮球运动员选材方法,能够有效评估篮球运动员运动能力.
In order to improve the prediction level of basketball players'talent selection,21 indicators such as body shape,sports quality,sports function and technical level were selected to form an evaluation system of basketball players'talent selection.By using the correlation analysis method in the grey system theory,the correlation degree of each material selection index was analyzed,and the core material selec⁃tion factors affecting the athletic ability of basketball players were selected.Based on machine learning theory to core material factors as the input vector,with expert evaluation of sports ability as the output vec⁃tor,established between basketball athletic ability and core material factor of the BP neural network pre⁃diction model,continuous training and study,through the network to find the core material factor and the intrinsic relationships between sport ability.The experimental results show that the basketball player selec⁃tion method based on BP neural system and grey degree model proposed in this study can effectively eval⁃uate the athletic ability of basketball players.
作者
陈熹
董阳
CHEN Xi;DONG Yang(Xuchang Vocational and Technical College,Xuchang 461000,China)
出处
《通化师范学院学报》
2020年第12期92-97,共6页
Journal of Tonghua Normal University
关键词
BP神经系统
灰色度模型
运动员选材
篮球
运动能力
BP nervous system
grey degree model
the selection of athletes
basketball
sports ability
