基于粗集理论的模糊神经网络建模方法研究

Research on Fuzzy Neural Network Modeling Method Based on Rough Set Theory

智能控制研究发展到了模糊神经网络阶段 ,其中 5层模糊神经网络结构的物理含义清晰 ,而 Max- Min模糊神经网络反应快 ,实时性强。在分析两者优缺点的基础上 ,提出了基于粗糙集构建模糊神经网络的方法 ,并通过比较 3种方法对同一个事例的建模 ,说明了基于粗糙集方法的优点。

The research of Intelligent Control has been developed into the stage of Fuzzy Neural Network. About the FNNs,Five Layers Fuzzy Neural Network is clear in its structure, while the Max-min Fuzzy neural Network responds fast and has good ability for real time control. In this paper, based on analysing their advantages and shortcomings, a modeling approach of Fuzzy Neural Network based on Rough Set is introduced. Moreover, by comparing the three modeling methods which are used to the same example respectively, the advantages of approach based on Rough Set is elucidated.