Multilevel weighted fuzzy reasoning with interaction

This paper presents an interactive weighted fuzzy reasoning algorithm for rule-based systems based on Interactive Weighted Fuzzy Petri Nets (IWFPN). The fuzzy production rules in the knowledge base of a rule-based system are modelled by IWFPN, where the weights appearing in the rules are represented by fuzzy numbers. In order to model and handle the interaction existing among attributes in a more flexible way, this paper also proposes a fuzzy number-valued fuzzy integral (called extended Choquet integral) to draw the reasoning conclusion, where the fuzzy measure refers to an extended g-lambda measure, or a nonadditive nonnegative fuzzy number-valued set function specified by a domain expert The proposed algorithm can allow the rule-based systems to perform fuzzy reasoning in a more intelligent manner.