BGrC for Superheated Steam Temperature System Modeling in Power Plant
Keming Xie, Gang Xie · 2006
As a new kind of soft computing method, Rough Set Theory (RST) has been successfully applied in many fields, however, most of its application is focus on the knowledge reduction algorithm that based on the classification. Granular computing (GrC) brings a new thought for problem solving, and it arose much interest since its appearance. This paper introduces GrC method into traditional RST knowledge reduction algorithm by the definition of binary granular matrix. The new algorithm makes the traditional knowledge reduction algorithm become simple matrix operation and it is successfully applied to model for the superheated steam temperature system in the Power Plant. Detailed description is given in this paper.