Method of Fault Intelligent Classification Based on Rough Set and Support Vector Machine
Xu Xi, Yao Qiong-hui, Min Shi · Computing Technology and Automation · 2006
A method based on rough set and support vector machine and applied for fault classification is proposed in this paper.Using the rough set reduction algorithm as the pretreatment of diagnosis data,it can get rid of redundant attributes of decision table.Then support vector machine is used the to fault classification modeling and forecast after rough set reduction.The method can reduce the dimensions of the fault diagnosis data and the complexity of the fault classification with SVM,and can not affect its classification performance.Applied to fault data classification of diesel engine,it can obtain the fault class fast and actually.