Approach for transformer fault diagnosis based on rough set and condition entropy
Hongwen Yan · Jisuanji gongcheng yu sheji · 2008
According to the changing tendency of the decision attributes given condition attributes and the frequency of attribute in dis-cernibility matrix,then a new attribute reduction algorithm based on information entropy and attribute frequency in discernibility matrix is proposed,then the rough set theory of automation knowledge acquisition is applied in transformer fault diagnosis in power system,the example shows that the proposed method reduces the redundancy of fault diagnosis information with high efficiency,and easy to be understood,it can also be applied in other field in power system.