Fuzzy Neural Petri Nets

Authors:
Hua Xu;Yuan Wang;Peifa Jia
Affiliations:
State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing, 100084, P.R. China;State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing, 100084, P.R. China and Department of Computer Science and Technology, Tsinghua University, Beijing, 100084 ...;State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing, 100084, P.R. China and Department of Computer Science and Technology, Tsinghua University, Beijing, 100084 ...
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Year:
2007

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Abstract

Fuzzy Petri net (FPN) is a powerful modeling tool for fuzzy production rules based knowledge systems. But it is lack of learning mechanism, which is the main weakness while modeling uncertain knowledge systems. Fuzzy neural Petri net (FNPN) is proposed in this paper, in which fuzzy neuron components are introduced into FPN as a sub-net model of FNPN. For neuron components in FNPN, back propagation (BP) learning algorithm of neural network is introduced. And the parameters of fuzzy production rules in FNPN neurons can be learnt and trained by this means. At the same time, different neurons on different layers can be learnt and trained independently. The FNPN proposed in this paper is meaningful for Petri net models and fuzzy systems.