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
Link To Document :
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