Hebei Sport University, Department of Sports Human Science, Shijiazhuan 050041, China.
Hebei Sport University, Department of Winter Sport, Shijiazhuang 050041, China.
J Healthc Eng. 2021 Sep 29;2021:2911025. doi: 10.1155/2021/2911025. eCollection 2021.
We study the rehabilitation training of damaged parts of ice and snow sports clock and ensure the physical safety of athletes. The results show that the RBF neural network updates the center, weight, and width of the radial basis function, and the predicted maximum compliance is 99%, and the minimum compliance is 93%. After many analysis times, the prediction results show that the difference between the predicted degree of conformity and the actual results is less than 8%. The RBF neural network is trained according to the risk database of sports injury, and the RBF neural network will output corresponding values to realize sports injury estimation. The experimental results show that the designed model has high precision and efficiency.
我们研究冰雪运动器材受损部位的康复训练，确保运动员的身体安全。结果表明，RBF 神经网络更新了径向基函数的中心、权重和宽度，预测的最大顺应性为 99%，最小顺应性为 93%。经过多次分析，预测结果表明，预测的一致性程度与实际结果之间的差异小于 8%。根据运动损伤风险数据库对 RBF 神经网络进行训练，RBF 神经网络将输出相应的值以实现运动损伤估计。实验结果表明，所设计的模型具有高精度和高效率。
