Models-based Optimization Methods for the Specication of Fuzzy Inference Systems in Discrete EVent Simulation

DOI

10.2991/eusflat.2011.6How to use a DOI?

Keywords

DEVS, Fuzzy Sets Theory, FIS, optimization models, iDEVS, DEVFIS

Abstract

Fuzzy Inference Systems (FIS) have the advantage of relying on the properties of Fuzzy Logic to represent imperfect information so gradually, and manipulate them from a linguistic description. This exibility of representation is more signicant for the study of complex systems. Our aims are to propose a formal approach for describing FIS as a Discrete Event System (DES), and to extend a DES in order to use the many advantages oered by FIS: exibility, easy implementation, robustness... In this paper, we present the extension of Discrete EVent system Specication (DEVS) formalism to represent FIS, and we propose a modular approach (DEVFIS) to use several optimization methods. We focus mainly on the used new aproach about using genetic algoritm in order to optimize the FIS.

Copyright

© 2011, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Paul-Antoine Bisgambiglia
AU  - Bastien Poggi
AU  - Céline Nicolai
PY  - 2011/08
DA  - 2011/08
TI  - Models-based Optimization Methods for the Specication of Fuzzy Inference Systems in Discrete EVent Simulation
BT  - Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-11)
PB  - Atlantis Press
SP  - 957
EP  - 964
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2011.6
DO  - 10.2991/eusflat.2011.6
ID  - Bisgambiglia2011/08
ER  -