Research on Optimization of Structures of Fuzzy Neural Petri Net

Fuzzy net is of advantages that every node and parameter has distinct physical meanings and can describe the proposition and subjection of Petri net. Neural net has the ability of learning and self-adaptation, so it can be possible that the proposition of input place converges to output transition. Petri net which has the structure of fuzzy net and neural net can describe output transition as the function of the proposition of place after being trained successfully. Based on Takagi-sugeno model, the next transition condition is reasoned by the known place set, vice versa, the all dynamic processes of this system can be identified. At last simulations attests this way effective and feasible by Matlab software.