摘要
旋转是乒乓球最核心的致胜因素,研究乒乓球的运动轨迹一定应考虑旋转因素。基于此,设计实验获得乒乓球精确的初始位置坐标、初始速度及方向、旋转速度及方向;将这9个初始数据作为神经网络的输入信息,将精确的落点坐标作为输出信息,利用人工神经网络算法探讨输入、输出信息间的相关性。实验结果显示:初始速度、旋转速度、初始位置坐标与球落点坐标之间存在相关性。
Rotation being the secret to success in table tennis, the trajectory prediction research hence should take the rotation into consideration. This study designed experiment to obtain the precise initial position coordinates, initial velocity and direction, rotating speed and direction. These nine initial data were taken as the input information of neural network and the precise placement coordinates as the output information. The correlation between input and output information is discussed by using artificial neural network algorithm thereafter. The experimental results show that the initial speed, rotation and coordinate with the ball placement coordinates are correlated.
作者
季云峰
黄睿
施之皓
任杰
JI Yunfeng;HUANG Rui;SHI Zhihao;REN Jie(China Table Tennis College,Shanghai University of Sport,Shanghai 200438,China;Institute of Artificial Intelligence,Shanghai University of Technology and Engineering,Shanghai 200093,China)
出处
《上海体育学院学报》
CSSCI
北大核心
2018年第6期98-103,共6页
Journal of Shanghai University of Sport
基金
上海市科学技术委员会科研计划项目(15490503100)
关键词
乒乓球
旋转
速度
落点坐标
轨迹预测
神经网络
table tennis
rotation
velocity
placement coordinates
trajectory prediction
neural network
