Improved modeling algorithm of fuzzy Petri net for fuzzy reasoning

This paper proposes an improved modeling algorithm based on modified fuzzy Petri net for fuzzy reasoning. The asynchronized property of token was neglected due to simple structures of fuzzy Petri net models for fuzzy reasoning in literatures. The property will cause uncertain results of reasoning for complex problems. The modeling algorithm aims mainly at solving this issue based on fuzzy Petri net whose arc power function, transition function and place capacity are modified. Compared with existing fuzzy Petri nets, the modified fuzzy Petri net can be used to reason according to inherent firing mechanism without additional control mechanism. The algorithm uses arc power and module replacement to deal with reasoning uncertainty and structure conflict. The validity of the algorithm for forward/backward reasoning is proved for acyclic fuzzy rule-based systems. An example is given to illustrate the validity of the proposed algorithm for reasoning.