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Journal of Computer Science and Technology

, Volume 11, Issue 2, pp 133–149 | Cite as

NNF and NNPrF — Fuzzy Petri Nets based on neural network for knowledge representation, reasoning and learning

  • Zhou Yi 
  • Wu Shilin 
Article

Abstract

This paper proposes NNF — a fuzzy Petri Net system based on neural network for proposition logic representation, and gives the formal definition of NNF. For the NNF model, forward reasoning algorithm, backward reasoning algorithm and knowledge learning algorithm are discussed based on weight training algorithm of neural network — Back Propagation algorithm.Thus NNF is endowed with the ability of learning a rule. The paper concludes with a discussion on extending NNF to predicate logic, forming NNPrF, and proposing the formal definition and a reasoning algorithm of NNPrF.

Keywords

Fuzzy Petri net system NNF NNPrF neural network forward reasoning backward reasoning learning 

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References

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Copyright information

© Science Press, Beijing China and Allerton Press Inc. 1996

Authors and Affiliations

  • Zhou Yi 
    • 1
  • Wu Shilin 
    • 1
  1. 1.Department of Computer ScienceFudan UniversityShanghai

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