Modeling, reasoning, and application of fuzzy Petri net model: a survey

A fuzzy Petri net (FPN) is a powerful tool to model and analyze knowledge-based systems containing vague information. This paper systematically reviews recent developments of the FPN model from the following three perspectives: knowledge representation using FPN, reasoning mechanisms using an FPN fr...

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Published inThe Artificial intelligence review Vol. 55; no. 8; pp. 6567 - 6605
Main Authors Jiang, Wei, Zhou, Kai-Qing, Sarkheyli-Hägele, Arezoo, Zain, Azlan Mohd
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.12.2022
Springer
Springer Nature B.V
Subjects
Artificial Intelligence
Big data
Computer Science
Explosions
Fault diagnosis
Fuzzy logic
Fuzzy Petri net
Industrial application
Industrial applications
Knowledge representation
Knowledge-based systems
Modeling
Modelling
Petri nets
Reasoning
Subject specialists
Surveys
Fuzzy Petri net
Reasoning
Modeling
Industrial application
Knowledge representation
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Summary:A fuzzy Petri net (FPN) is a powerful tool to model and analyze knowledge-based systems containing vague information. This paper systematically reviews recent developments of the FPN model from the following three perspectives: knowledge representation using FPN, reasoning mechanisms using an FPN framework, and the latest industrial applications using FPN. In addition, some specific modeling and reasoning approaches to FPN to solve the ‘state-explosion problem’ are illustrated. Furthermore, detailed analysis of the discussed aspects are shown to reveal some interesting findings, as well as their developmental history. Finally, we present conclusions and suggestions for future research directions.
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ISSN:0269-2821
1573-7462
1573-7462
DOI:10.1007/s10462-022-10161-0