制动器制动最高温度径向基神经网络预测

Prediction of brake maximum temperature based on radial basis function neural network

神经网络具有智能化和快速学习能力,在复杂动态系统预测方面具有十分广泛的应用,文章基于径向基函数神经网络,对制动器制动最高温度预测问题进行了研究。通过仿真模拟验证了径向基函数神经网络在逼近与预测方面的强大功能,同时通过对径向基函数分布密度的优化得到了用于制动器制动最高温度预测的神经网络预测系统,同时对制动温度的预测,得到了精度较高的预测结果。文章的研究对于制动器制动性能预测具有一定的参考。

The neural network has the ability of intelligent and fast learning and is widely used in the prediction of complex dynamic systems.Based on radial basis function neural network,this paper studies the problem of braking maximum temperature prediction.The powerful function of radial basis function neural network is verified for approximation and prediction by simulation.At the same time,the neural network prediction system used to predict the brake maximum temperature is obtained by optimizing the distribution density of radial basis function,and the obtained prediction results has a high precision for braking temperature prediction.The research has some reference for brake performance prediction.