Development of a forecasting agent based on a fuzzy neural Petri net for predicting abnormal situations in automation systems
Alexey Sukonschikov, А.Н. Швецов, I. A. Andrianov, Dmitry Kochkin, Sergey A. Sorokin · AIP conference proceedings · 2021
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.