Fault Diagnosis Based on Rough Set Neural Networks and Data Fusion
Shanxia Wang · Microcomputer Development · 2005
The neural network is a kind of important method that break down the intelligent diagnosis problem of complex system.The rough set theory to them handles a kind of technique of the not complete information. In this paper the intelligent diagnosis problem of complex system is the research object. The theory,method, system and practice of intelligent diagnosis problem based on neural networks, rough set theory and date fusion are systematically discussed.In this paper the key idea is as follows: On the basis of fault diagnosis network model,knowledge representation system of rough set theory is taken as a major tool to simplify the complex combine neural network and in which unecessary properties are eliminated .The method overcomes some shortcomings,such as network scale is too large and the rate of classification is slow.Based on rough set combine neural network model is presented. Then, a satisfying result is described by using data fusion. Finally an example of fault diagnosis shows validity of this method.