世界优秀男子跳高运动员身体素质与专项成绩相关关系的递归神经网络模型构建

借助递归神经网络强大的动态映射能力,提出了反映世界优秀男子跳高运动员身体素质与专项成绩相关关系的递归神经网络模型.该模型克服了多元回归模型和灰色模型的缺点,在不需要事先确定模型数学表达形式的条件下,更为准确地映射出运动员身体素质训练水平与专项成绩之间的函数关系.并且运用建立起的神经网络模型,绘制了素质训练水平与专项成绩之间的关系曲线.从而为跳高运动员进行科学训练提供了理论依据.

Construction of Recurrent Neural Network Model for Relationship between Specific Performance and Physical Fitness of Top High Jumpers in the World

Using the strong dynamic mapping of recurrent neural network,a recurrent neural network model for relationship between specific performance and physical fitness of top high jumpers in the world is proposed.This model overcomes the shortcomings of the multiple regression model and gray model,and thus it can more accurately reflect the function relation between the physical fitness and specific performance.Furthermore using this neural network model,the relationship curve between specific performance and physical fitness is drawn.Then the high jumpers may be trained scientifically by the use of this relationship curve.