Application Attributes Reduction of Rough Set in Power System for Fault Diagnosis

The fault in power system cannot be completely avoided. Rough set is a generalization of crisp rough set to deal with data sets with real value attributes. Attribute reduction is very important in rough set-based data analysis because it can be used to simplify the induced decision rules without reducing the classification accuracy. In this paper, we developed a method to resolve fault localization problems in power system. The notion of reduct plays a key role in rough set-based attribute reduction. In rough set theory, a reduct is generally defined as a minimal subset of attributes that can classify the same domain of objects as unambiguously as the original set of attributes. Experimental results imply that our algorithm of attribute reduction with distribution of electricity feasible and valid.