Knowledge-base reduction based on rough set techniques

Knowledge acquisition is one of the most difficult tasks during the construction of an expert system. Usually, the experts have difficulty in explaining to the knowledge engineers how they solve a given problem. This fact may result in superfluous information about some specific points, while in other points, only an incomplete set of information is available to prepare the knowledge base. This paper presents a contribution to help knowledge engineers to manipulate and reduce knowledge bases for power system operation problems using a systematic approach. The approach is based on rough set theory. An illustrative example is presented in this paper.