NDLI: Fuzzy Petri nets for rule-based decisionmaking

Content Provider	IEEE Xplore Digital Library
Author	Looney, C.G.
Copyright Year	1971
Abstract	The technique of fuzzy reasoning by transformations of fuzzy truth state vectors by fuzzy matrices is extended to Petri nets. The result is a novel type of neural network in which the transition bars serve as the neutrons, and the nodes are conditions. Conditions may be conjuncted and disjuncted in a natural way to allow the firing of the neurons. The neuron fires to feed the implication truths into one or more consequent conditions when the MIN of the truth values of the antecedent conditions is greater than the neuron threshold. Disjunctions are also modeled in a natural way. Modifications are made to the usual Petri model to allow fuzzy rule-based reasoning by propositional logic. First, fuzzy values are allowed for rules and truths of conditions that appear in rules. Next, multiple copies, rather than the original, of the fuzzy truth tokens are passed along all arrows that depart a node or transition bar where the truth resides. An algorithm is presented for reasoning using these networks, as well as a simple example for exercising the algorithm. Abduction may be done analogously be reversing all arrows and propagating truth tokens backwards.<>
Starting Page	178
Ending Page	183
Page Count	6
File Size	790282
File Format	PDF
ISSN	00189472
Volume Number	18
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1988-01-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Petri nets Fuzzy logic Fuzzy reasoning Expert systems Fuzzy control Neural networks Neurons Mathematical model Equations Control systems
Content Type	Text
Resource Type	Article
Subject	Engineering

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