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季云峰, 黄睿, 施之皓, 任杰. 乒乓球精确旋转、速度及落点数据的人工神经网络模型研究[J]. 上海体育学院学报 , 2018, 42(6): 98-103. DOI: 10.16099/j.sus.2018.06.014
引用本文: 季云峰, 黄睿, 施之皓, 任杰. 乒乓球精确旋转、速度及落点数据的人工神经网络模型研究[J]. 上海体育学院学报 , 2018, 42(6): 98-103. DOI: 10.16099/j.sus.2018.06.014
JI Yunfeng, HUANG Rui, SHI Zhihao, REN Jie. Artificial Neural Network Model for the Data of Precise Rotation, Velocity and Placement in Table Tennis[J]. Journal of Shanghai University of Sport, 2018, 42(6): 98-103. DOI: 10.16099/j.sus.2018.06.014
Citation: JI Yunfeng, HUANG Rui, SHI Zhihao, REN Jie. Artificial Neural Network Model for the Data of Precise Rotation, Velocity and Placement in Table Tennis[J]. Journal of Shanghai University of Sport, 2018, 42(6): 98-103. DOI: 10.16099/j.sus.2018.06.014

乒乓球精确旋转、速度及落点数据的人工神经网络模型研究

Artificial Neural Network Model for the Data of Precise Rotation, Velocity and Placement in Table Tennis

  • 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。

     

    Abstract: 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.

     

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