The Department of Physical Education, Peking University, Beijing 100871, China.
Sports Training Institute, Shenyang Sport University, Shenyang 110120, China.
Comput Intell Neurosci. 2021 Sep 22;2021:9497388. doi: 10.1155/2021/9497388. eCollection 2021.
The traditional basketball teaching mode cannot meet the needs of students for the basic cooperation of basketball tactics. Therefore, a basic cooperation teaching system of basketball tactics based on artificial neural network is studied and designed. The system has a professional basketball game video tactical learning module. The events in the basketball game video are classified through a convolutional neural network and combined with the explanation of teachers to make the students have an intuitive understanding of the basic cooperation of basketball tactics and then design the basketball game module based on a BP neural network to provide students with an online basketball tactics training platform. Finally, the teacher scores the performance of the actual on-site training students in the basic cooperation of basketball tactics through the tactical scoring module on the system. The results show that after the introduction of global and collective motion patterns, the classification accuracy of the convolutional neural network is improved by 22.48%, which has significant optimization. The average accuracy of basketball game video event classification is 62.35%, and the accuracy of snatch event classification is improved to 95.28%. The recognition rate of the BP neural network combined with momentum gradient descent method is 75%, the number of weight adjustment is less, and the memory is small while ensuring fast running speed. Students who accept the basic basketball tactics cooperation teaching system based on the artificial neural network for basketball teaching have an overall score of 27.99 ± 2.11 points The overall score of exchange defense cooperation was 24.12 ± 2.03, which was higher than that of the control group. The above results show that the basketball tactical basic cooperation teaching system based on the artificial neural network has a good teaching effect in improving students' basketball tactical basic cooperation ability.
传统的篮球教学模式已经不能满足学生对篮球战术基本配合的需求。因此,研究并设计了一种基于人工神经网络的篮球战术基本配合教学系统。该系统具有专业的篮球比赛视频战术学习模块。通过卷积神经网络对篮球比赛视频中的事件进行分类,并结合教师的讲解,使学生对篮球战术的基本配合有直观的了解,然后基于 BP 神经网络设计篮球比赛模块,为学生提供在线篮球战术训练平台。最后,教师通过系统中的战术评分模块对实际现场训练学生的篮球战术基本配合表现进行评分。结果表明,引入全局和集体运动模式后,卷积神经网络的分类准确率提高了 22.48%,具有显著的优化效果。篮球比赛视频事件分类的平均准确率为 62.35%,抢球事件的分类准确率提高到 95.28%。结合动量梯度下降法的 BP 神经网络的识别率为 75%,调整权重的次数较少,记忆量小,同时保证了快速的运行速度。接受基于人工神经网络的篮球基本战术配合教学系统进行篮球教学的学生,整体得分为 27.99±2.11 分,交换防守配合的整体得分为 24.12±2.03,均高于对照组。以上结果表明,基于人工神经网络的篮球战术基本配合教学系统在提高学生篮球战术基本配合能力方面具有良好的教学效果。