• DocumentCode
    2312901
  • Title

    Fuzzy inference models for Discrete EVent systems

  • Author

    Bisgambiglia, P.-A. ; Capocchi, L. ; Bisgambiglia, P. ; Garredu, S.

  • Author_Institution
    Univ. of Corsica, Ajaccio, France
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    For several years, we worked to improve a discrete events modeling formalism: called DEVS. Having defined a method to take into account the inaccuracies iDEVS, in this paper, we present the second part of our research work. Generally, our approach is to associate the DEVS formalism with an object class, which allows using it to new fields of study, and in our case fuzzy systems. This paper describes a new modeling methodology. It allows to modeling and to use fuzzy inference systems (FIS) with DEVS formalism in order to perform the control or the learning on systems described incompletely or with linguistic data. The advantages of this method are numerous: to extend the DEVS formalism to other application fields; to propose new DEVS models for fuzzy inference; to provide users with simple and intuitive modeling methods. Throughout this paper we describe the tools and methods which were developed to make possible the combination of these two approaches.
  • Keywords
    discrete event systems; fuzzy set theory; fuzzy systems; inference mechanisms; DEVS formalism; discrete event systems; fuzzy inference models; fuzzy inference systems; Fuzzy set theory; Fuzzy sets; Integrated circuit modeling; Mathematical model; Object oriented modeling; Pragmatics; Takagi-Sugeno model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-6919-2
  • Type

    conf

  • DOI
    10.1109/FUZZY.2010.5584707
  • Filename
    5584707