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 non-additive 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.