FUZZY PETRI-NET REPRESENTATION AND REASONING METHODS FOR RULE-BASED DECISION-MAKING SYSTEMS

In this paper, we propose a fuzzy Petri net model for a rule-based dec ision making system which contains uncertain conditions and vague rule s. Using the transformation method introduced in the paper, one can ob tain the fuzzy Petri net of the rule-based system. Since the fuzzy Pet ri net can be represented by some matrices, the algebraic form of a st ate equation of the fuzzy Petri net is systematically derived. Both fo rward and backward reasoning are performed by using the state equation s. Since the proposed reasoning methods require only simple arithmetic operations under a parallel rule firing scheme, it is possible to per form real-time decision making with applications to control systems an d diagnostic systems. The methodology presented is also applicable to classical (nonfuzzy) knowledge base systems if the nonfuzzy system is considered as a special case of a fuzzy system with truth values being equal to the extreme values only. Finally, an illustrative example of a rule-based decision making system is given for automobile engine di agnosis.