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Predictability in Probabilistic Discrete Event Systems

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Book cover Soft Methods for Data Science (SMPS 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 456))

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Abstract

Predictability is a key property allowing one to expect in advance the occurrence of a fault in a system based on its observed events. Existing works give a binary answer to the question of knowing whether a system is predictable or not. In this paper, we consider discrete event systems where probabilities of the transitions are available. We show how to take advantage of this information to perform a Markov chain-based analysis and extract probability values that give a finer appreciation of the degree of predictability. This analysis is particularly important in case of non predictable systems.

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Notes

  1. 1.

    To simplify figures, we represent a state name \(x_i\) by its index i.

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Author information

Authors and Affiliations

  1. LSIS, CNRS, University Aix-Marseille, Marseille, France

    Farid Nouioua

  2. LRI, CNRS, University Paris-Sud, University Paris-Saclay, Orsay, France

    Philippe Dague

  3. LRI, CentraleSupélec, CNRS, University Paris-Saclay, Orsay, France

    Lina Ye

Authors
  1. Farid Nouioua
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  2. Philippe Dague
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  3. Lina Ye
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Corresponding author

Correspondence to Farid Nouioua .

Editor information

Editors and Affiliations

  1. Department of Statistical Sciences, Sapienza University of Rome, Rome, Italy

    Maria Brigida Ferraro

  2. Department of Statistical Sciences, Sapienza University of Rome, Roma, Italy

    Paolo Giordani

  3. Dept of Basic & Applied Sciences Engg, Sapienza University of Rome, Rome, Italy

    Barbara Vantaggi

  4. Dept of Stoc Metds,Polish Academy of Sci, Systems Research Institute, Warsaw, Poland

    Marek Gagolewski

  5. Dept of Statis&OR and MD, Univ de Oviedo, Oviedo, Spain

    María Ángeles Gil

  6. Dept of Stoc Metds,Polish Aca of Science, Systems Res Inst, Warsaw, Poland

    Przemysław Grzegorzewski

  7. Sys Res Inti, Dept of Stoch Methods, Polish Acadmy Sci in Warsaw, Warsaw, Poland

    Olgierd Hryniewicz

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© 2017 Springer International Publishing Switzerland

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Nouioua, F., Dague, P., Ye, L. (2017). Predictability in Probabilistic Discrete Event Systems. In: Ferraro, M., et al. Soft Methods for Data Science. SMPS 2016. Advances in Intelligent Systems and Computing, vol 456. Springer, Cham. https://doi.org/10.1007/978-3-319-42972-4_47

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  • DOI: https://doi.org/10.1007/978-3-319-42972-4_47

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42971-7

  • Online ISBN: 978-3-319-42972-4

  • eBook Packages: EngineeringEngineering (R0)

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