A New Fuzzy Reasoning Model for Decision Support System

Abstract

This paper proposes a new fuzzy reasoning model, involved the knowledge representation sub–model based on synthetic language system, the operators and the inference rules it uses, and, the meta–rules for the firing rule selection. The model is used for the knowledge – based decision support to make DSS enable to support human decision making process in which information coming from real – world is imperfect. The new model is a combination of fuzzy production model based on Zadeh's fuzzy logic and traditional production model based on traditional two–valued or multi–valued logic. The new model is efficient in inference with fuzzy information by means of the combining the inference rules of fuzzy logic with the variety of the matching rules of the traditional production systems and the quantifier – tables, make it possible for explaining the inference process and inference consequences, that is, the decision support process.