The Strategies of Optimizing Fuzzy Petri Nets by Using an Improved Genetic Algorithm

Abstract: It is very important for constructing a FPN (fuzzy petri net) to accurately find out all parameters of fuzzy production rules. In this paper, an improved genetic algorithm is introduced into the process of exploring the optimal parameters of a modified FPN. Realization of the algorithm does not depend on experiential data and requirements for the initial input of the FPN are not stringent. Simulation experiment shows that the parameters trained by the above algorithm are highly accurate and the FPN model constructed by these parameters possesses strong generalizing capability and self-adjusting purpose.
Keywords: FPN; fuzzy production rule; fuzzy reasoning; improved genetic algorithm
Author: Li Yang, Yue Xiao-bo
Journal Code: jptkomputergg160111

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