Fuzzy Petri nets for rule-based decisionmaking

C.G. Looney

doi:10.1109/21.87067

Fuzzy Petri nets for rule-based decisionmaking

IEEE Transactions on Systems Man and Cybernetics ◽

10.1109/21.87067 ◽

1988 ◽

Vol 18 (1) ◽

pp. 178-183 ◽

Cited By ~ 310

Author(s):

C.G. Looney

Keyword(s):

Petri Nets ◽

Rule Based ◽

Fuzzy Petri Nets

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A Rule-Based Decision-Making Diagnosis System to Evaluate Arteriovenous Shunt Stenosis for Hemodialysis Treatment of Patients Using Fuzzy Petri Nets

IEEE Journal of Biomedical and Health Informatics ◽

10.1109/jbhi.2013.2279595 ◽

2014 ◽

Vol 18 (2) ◽

pp. 703-713 ◽

Cited By ~ 29

Author(s):

Wei-Ling Chen ◽

Chung-Dann Kan ◽

Chia-Hung Lin ◽

Tainsong Chen

Keyword(s):

Decision Making ◽

Petri Nets ◽

Arteriovenous Shunt ◽

Rule Based ◽

Diagnosis System ◽

Hemodialysis Treatment ◽

Fuzzy Petri Nets

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Fuzzy Petri nets for rule-based pattern classification

IEEE 2002 International Conference on Communications, Circuits and Systems and West Sino Expositions ◽

10.1109/icccas.2002.1179002 ◽

2003 ◽

Cited By ~ 2

Author(s):

Xi Chen ◽

Dongming Jin ◽

Zhijian Li

Keyword(s):

Petri Nets ◽

Pattern Classification ◽

Rule Based ◽

Fuzzy Petri Nets

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FUZZY PETRI NETS FOR MODELING RULE-BASED REASONING

International Journal of Artificial Intelligence Tools ◽

10.1142/s0218213098000226 ◽

1998 ◽

Vol 07 (04) ◽

pp. 463-485 ◽

Cited By ~ 12

Author(s):

JONATHAN LEE ◽

KEVIN F. R. LIU ◽

WEILING CHIANG

Keyword(s):

Petri Nets ◽

Fuzzy Rule ◽

Fuzzy Reasoning ◽

Fuzzy Rules ◽

Rule Based ◽

Imprecise Information ◽

Fuzzy Petri Nets ◽

Reasoning Algorithm ◽

Modeling Rule

In this paper, a fuzzy Petri nets for modeling fuzzy rule-based reasoning is proposed to bring together the possibilistic entailment and the fuzzy reasoning to handle uncertain and imprecise information. The three key components in our fuzzy rule-based reasoning: fuzzy propositions, truth-qualified fuzzy rules, and truth-qualified fuzzy facts, can be formulated as fuzzy places, uncertain transitions, and uncertain fuzzy tokens, respectively. Four types of uncertain transitions, inference, aggregation, duplication and aggregation-duplication transitions, are introduced to meet the mechanism of fuzzy rule-based reasoning. A reasoning algorithm based on fuzzy Petri nets is also presented to improve the efficiency of fuzzy rule-based reasoning. The reasoning algorithm is consistent with not only the rule-based reasoning but also the execution of Petri nets.

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