体育成绩测试中BP神经网络的应用分析

Application of BP Neural Network in Sports Achievement Test

基于MATLAB建立了一种BP神经网络算法模型,介绍了其计算流程和计算代码。该BP神经网络模型在运动员3000 m长跑成绩仿真测试中表现出了较高的准确度和可信度,5次实验的平均误差仅为0.18 min,最小误差仅为0.1 min。还利用该BP神经网络模型研究了运动晨脉、血压、血氧与体育成绩之间的关系。其中晨脉和血压稳定状态下,运动员的成绩较为稳定,且出现提升趋势;其收缩压和舒张压均处于临界值时,运动员的状态较为兴奋,相应成绩较好。

A BP neural network model was established based on MATLAB,and its calculation process and code were introduced.The BP neural network model showed high accuracy and credibility in the simulation test of 3000 meter long-distance running performance.The average error of five experiments was only 0.18 min,and the minimum error was only 0.1 min.The BP neural network model was used to study the relationship between morning pulse,blood pressure,blood oxygen and sports performance.In the stable state of morning pulse and blood pressure,the performance of athletes was relatively stable,and there was an upward trend;when the systolic and diastolic blood pressure were at the critical value,the athletes were relatively excited and the corresponding results were better.