足球运动员训练机能监控系统设计

Design of football player training function monitoring system

针对目前传统的足球运动员训练机能监控方法存在的缺乏科学高效的评价、运动训练数据信息反馈速度慢等问题,研究利用时间序列分析方法,对足球运动员运动训练的机能变化进行智能监控与预测,应用决策支持系统构建完整的足球运动员训练机能监控决策支持系统。研究结果显示,经综合考虑,时间序列模型选定 AMA 1,1 模型。在该模型的预测中,血红蛋白的平均真实值为153 g/L,平均预测值为152 g/L,残差在[-1,1]。综上所述,研究提出的足球运动员训练机能监控决策支持系统具有较高的准确性。

In view of the problems existing in the current traditional monitoring methods of football players’ training function, such as the lack of scientific and efficient evaluation, diagnosis and evaluation, and the slow feedback speed of sports training data information, this paper studies the use of time series analysis method to intelligently monitor and predict the changes of football players’ training function, and applies the decision support system to build a complete football players’ training function monitoring decision support system. The research results show that the time series model is selected after comprehensive consideration. In the prediction of this model, the average true value of hemoglobin is 153 g/L, the average predicted value is 152g/L, and the residual is in the range of-1~1. To sum up, the soccer player training function monitoring decision support system proposed in the study has high accuracy.