Intuitionistic Fuzzy Petri Nets Model and Reasoning Algorithm

To the limitation of fuzzy Petri nets single membership, the intuitionistic fuzzy Petri nets model and reasoning algorithm is proposed by combining the advantage of intuitionistic fuzzy sets with Petri nets. In the model, the confidence degree and threshold of the transition as well as the token value of each place are represented by intuitionistic fuzzy number. This model can solve the problem of each importing place with asymmetrical weight to one transition by taking account into the weighted parameter, and it can be condensed by the output matrix joining the confidence degree parameter. Furthermore, the efficiency of the reasoning is improved due to the parallel operation ability of Petri nets, the reasoning result is more believable and precise for the effect of the nonmembership parameter. Finally, the feasibility and validity of the proposed inference model are presented by an instance.