蔗糖结晶中的BP网络的算法选择及改进

推导了隐层节点和输出节点的学习及修正公式，选择了初始权值、学习速率和期望误差等相关学习参数，结合结晶工段实际进行了网络训练。为加快网络的收敛，在保证系统稳定的基础上，提出了S 函数输出限幅和变步长法两种改进方案。采用改进的BP 算法对此BP 网络进行了训练，得到的ANN 网络训练输出值与实际输出值非常逼近。
关键词：BP 算法；网络训练；收敛；修正

Algorithmic Choice and Betterment in the BP Network ofCane Sugar Crystallization YANG Jie1,2, YAN Qingdong1 (1. School of Communication Machinery and Civil Engineering, Southwest Forestry University, Kunming, Yunnan 650224, China; 2. School of Mechanical and Vehicle Engineering, Beijing Institute of Technology, Beijing 100081, China ) Abstract: The learning and amendatory formulae of the hidden layer nodes and deferent nodes were deduced. Initial weight value，learning rate and expectation error etc. correlative learning parameters were selected, then the BP network was trained integrating practical instance. In order to quicken convergence, S function output violent change and method of changing step length which two improved project were brought forward in the basis of system stabilization. And the BP network was trained by using improved algorithm, the result showed that ANN
model output extremely approximated to practical output.
Key words: BP algorithm; Network training; Convergence；Amendment