Diagnosis Using Incomplete Model in Fuzzy Discrete Event System: Application to Crisis Management

Moussa Traoré, Eric Chatelet (), Eddie Soulier () and Hossam Gaber
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Moussa Traoré: LM2S - Laboratoire Modélisation et Sûreté des Systèmes - ICD - Institut Charles Delaunay - UTT - Université de Technologie de Troyes - CNRS - Centre National de la Recherche Scientifique
Eric Chatelet: LM2S - Laboratoire Modélisation et Sûreté des Systèmes - ICD - Institut Charles Delaunay - UTT - Université de Technologie de Troyes - CNRS - Centre National de la Recherche Scientifique
Eddie Soulier: Tech-CICO - TECHnologies pour la Coopération, l’Interaction et les COnnaissances dans les collectifs - ICD - Institut Charles Delaunay - UTT - Université de Technologie de Troyes - CNRS - Centre National de la Recherche Scientifique - CNRS - Centre National de la Recherche Scientifique
Hossam Gaber: UOIT = Ontario Tech University - University of Ontario Institute of Technology

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Abstract: This paper presents a novel diagnosis approach for crisis management using fuzzy discrete event system (model). The method exploits the output events and membership value of each active state as input events of the diagnoser (diagnosis module). In our work the choice of fuzzy system representation is justified by the assumption that, during crisis management, the stress and/or impact emotion of the teams involved in crisis management must be taken into account and the evolution of the situation may not necessarily in one active state. The membership value generated by the model can be used for the possible control action during the crisis management.

Keywords: discrete event systems; emergency management; fuzzy set theory (search for similar items in EconPapers)
Date: 2014-12-03
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Published in 2014 13th International Conference on Machine Learning and Applications (ICMLA), Dec 2014, Detroit, United States. pp.432-440, ⟨10.1109/ICMLA.2014.109⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-02881959

DOI: 10.1109/ICMLA.2014.109

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