Improved algorithm on rule-based reasoning systems modeled by fuzzy Petri nets

Abstract

In this paper, we propose a complete and efficient algorithm to perform the fuzzy inference of a rule-based system modeled by Fuzzy Petri Nets (FPN). The algorithm is developed to simulate the inference process from the starting propositions to the goal propositions. The structures of the FPN are in more generic forms, compared to those applied in previous papers. The formal description of models and the fuzzy reasoning algorithm are described in detail, with several illustration examples. The differences between other algorithms are also presented.