Fuzzy Petri nets for rule-based decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
A G-Net Model for Knowledge Representation and Reasoning
IEEE Transactions on Knowledge and Data Engineering
Knowledge Representation Using Fuzzy Petri Nets
IEEE Transactions on Knowledge and Data Engineering
Weighted Fuzzy Reasoning Using Weighted Fuzzy Petri Nets
IEEE Transactions on Knowledge and Data Engineering
A Parallel Backward Reasoning Study Using Fuzzy Petri Net
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 03
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy backward reasoning using fuzzy Petri nets
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Modeling uncertainty reasoning with possibilistic Petri nets
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Intelligent decision making in disassembly process based on fuzzy reasoning Petri nets
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Interval-valued fuzzy backward reasoning
IEEE Transactions on Fuzzy Systems
Fuzzy reasoning supported by Petri nets
IEEE Transactions on Fuzzy Systems
Computers and Industrial Engineering
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An alterative approach to the backward reasoning is presented. In classical reasoning, both users and developers of many expert systems are dedicated to the forward reasoning. However, in many newly arising expert systems such as various diagnosis systems, the backward reasoning is of special interest and often preferable. In this paper, the fuzzy Petri nets are used to analytically represent the knowledge of fault diagnosis in manufacturing systems and an iterative algorithm based on max-algebra is used to deduce the consequence-antecedent relationship between their manifestation and antecedent. Finally, the legitimacy and efficiency of the proposed approach are proved and validated by an illustrative example.