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ESANN
2008

Petri nets design based on neural networks

11 years 3 months ago
Petri nets design based on neural networks
Petri net faulty models are useful for reliability analysis and fault diagnosis of discrete event systems. Such models are difficult to work out as long as they must be computed according to alarm propagation. This paper deals with Petri net models synthesis and identification based on neural network approaches, with regard to event propagation and to state propagation dataset. A learning neural algorithm is proposed to build Petri net models, these models are suitable for the diagnosis of discrete event systems.
Edouard Leclercq, Souleiman Ould el Medhi, Dimitri
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where ESANN
Authors Edouard Leclercq, Souleiman Ould el Medhi, Dimitri Lefebvre
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