Development of a forecasting agent based on a fuzzy neural Petri net for predicting abnormal situations in automation systems

Development of a forecasting agent based on a fuzzy neural Petri net for predicting abnormal situations in automation systems

This article examines the issues of modeling a forecasting agent based on extensions of Petri nets. For this, a new class of Petri nets, fuzzy-neural Petri nets, was developed. It made it possible to build a model for predicting a change in the situation from standard to boundary and abnormal. The i...

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Hauptverfasser: Sukonschikov, A. A., Shvetsov, A. N., Andrianov, I. A., Kochkin, D. V., Sorokin, S. A.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Artificial neural networks
Forecasting
Fuzzy logic
Mathematical models
Petri nets
Software
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Beschreibung
Zusammenfassung:This article examines the issues of modeling a forecasting agent based on extensions of Petri nets. For this, a new class of Petri nets, fuzzy-neural Petri nets, was developed. It made it possible to build a model for predicting a change in the situation from standard to boundary and abnormal. The implementation of this model in the CPN Tools software package is also considered.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0071782