WEIGHTED FUZZY PRODUCTION RULES

Most of the research works on fuzzy production rules (FPRs) show that its knowledge representation power suffers from a serious shortcoming in that all propositions in the antecedent part are assumed to have eq ual importance (the lack of ''local weight'' concept), and that a numb er of rules executed in an inference path leading to a specified goal or the same rule employed in various inference paths leading to distin ct final goals may have relative degrees of importance, has not been e xplored (the lack of ''global weight'' concept). This paper presents a weighted FPR (WFPR) incorporating the concepts of local and global we ights. An improved method to compute the fuzzy value and the certainty factor of the consequent assertion and a better way to interpret the linguistic meaning of the consequent are proposed for this WFPR. Our a pproach offers the advantages of enhancing the knowledge representatio n power of a FPR, reducing the undesirable effects when computing the certainty factor of the consequent part by generalizing the traditiona l method of computation, and overcoming the tedious steps involved in Zadeh's compositional rule of inference (CRI) method. As far as interp retation of the linguistic meaning of the consequent part is concerned , our method is found to be better than the ad hoc approach of CRI-bas ed methods. (C) 1997 Elsevier Science B.V.