A MULTILEVEL WEIGHTED FUZZY-REASONING ALGORITHM FOR EXPERT-SYSTEMS

The applications of fuzzy production rules (FPR's) are rather limited if the relative degree of importance of each proposition in the antece dent contributing to the consequent (i.e., the weight) is ignored or a ssumed to be equal, Unfortunately, this is the case for many existing FPR's and most existing fuzzy expert system development shells or envi ronments offer no such functionality for users to incorporate differen t weights in the antecedent of FPR's, This paper proposes to assign a weight parameter to each proposition in the antecedent of a FPR and a new fuzzy production rule evaluation method (FPREM) which generalizes the traditional method by taking the weight factors into consideration is devised, Furthermore, a multilevel weighted fuzzy reasoning algori thm (MLWFRA) incorporating this new FPREM, which is based on the reach ability and adjacent place characteristics of a fuzzy Petri net, is de veloped, The MLWFRA has the advantages that i) it offers multilevel re asoning capability; ii) it allows multiple conclusions to be drawn if they exist; iii) it offers a new fuzzy production rule evaluation meth od; and iv) it is capable of detecting cycle rules.