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A. El Moudni

Researcher at Universite de technologie de Belfort-Montbeliard

Publications -  72
Citations -  644

A. El Moudni is an academic researcher from Universite de technologie de Belfort-Montbeliard. The author has contributed to research in topics: Petri net & Stochastic Petri net. The author has an hindex of 15, co-authored 72 publications receiving 591 citations. Previous affiliations of A. El Moudni include École Normale Supérieure.

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Continuous and timed Petri nets for the macroscopic and microscopic traffic flow modelling

TL;DR: The proposed models suggest a mathematical framework for the analysis and control design in urban and interurban networks and suitable to represent the traffic flow either from a macroscopic point of view where only global variables are observed or from a microscopic one where the individual trajectories of vehicles are discussed.
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Optimal control of a particular class of singularly perturbed nonlinear discrete-time systems

TL;DR: A trajectory approximation result based on the decomposition of the model into reduced and boundary layer models is given, used to analyze optimal control via maximum principle of discrete-time nonlinear systems which depend on a small parameter.
Proceedings ArticleDOI

Continuous Petri nets models for the analysis of traffic urban networks

TL;DR: A model of VCPN is suggested for the analysis and control design in urban and interurban networks and provides representation for both motorway corridors and complex road junctions.
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Firing and enabling sequences estimation for timed Petri nets

TL;DR: This work deals with the estimation of firing and enabling sequences for timed transition PNs with unknown time delays with exact and approximated solutions that are described.
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Reliability analysis of a mechanical contact between deformable solids

TL;DR: In this paper, a new reliability analysis of a mechanical contact is presented, where a reliability-mechanical combination based on an augmented Lagrangian method and a response surface method is proposed to compute the failure probability of this nonlinear problem.