摘要
文中首先对标准的BP算法进行了分析.然后在此基础上提出了通过模糊规则推理动态调整学习率和动量因子的改进的方法,并通过模糊推理系统实现了BP算法的模糊控制.最后通过实例将该算法与标准BP算法和Vogl改进的算法进行了比较,实验结果表明通过模糊推理来改善神经网络的BP算法性能是一种很有前途的方法.
An analysis is made first of a standard BP algorithm,and then an improved method is proposed,which is meant to dynamically adjust learning rate and momentum factor by means of fuzzy inference.The fuzzy control of BP algorithm is thus achieved in the fuzzy inference system.Finally,examples are used to compare this fuzzy controlled BP algorithm with the standard BP algorithm and Vogl's improved algorithm.The experimental results indicate that it is a method of great promise to improve the performance of BP algorithm with the help of fuzzy inference.
出处
《计算机研究与发展》
EI
CSCD
北大核心
1998年第8期689-693,共5页
Journal of Computer Research and Development
基金
国家自然科学基金
上海铁道大学青年基金
上海市重点学科项目基金