BP神经网络在电池分选中的应用

The Application of BP Nerual Network in Battery-sorting

针对电池分选中，由于输入技术参数存在噪声而引起误选率过高的问题，以 ＢＰ（ｂａｄｋ－ｐｒｏｐａｇａｔｉｏｎ）神经网络为基础，使用抽样学习的方法，提出了多参数输入的电池分选方案．实验结果表明，该方法能在技术参数存在噪声的情况下，通过网络训练可减小分选误差．

In the course of battery-sorting, the ratio of wrong to correct is high because there is noise in input-parameter. In this paper, a new method for sorting batteries, in which sampling study is used, based on BP neural newtwork, is presented. The result explains that although there is noise in input-parameter, the ratio of wrong is decreased through sampling study, in the trained neural network.