title: |
Models-based Optimization Methods for the Specication of Fuzzy Inference Systems in Discrete EVent Simulation |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
| pages: | 957 - 964 | |
DOI: |
To be assigned soon (how to use a DOI) | |
author(s): |
P.-A. Bisgambiglia, B. Poggi, C. Nicolai |
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publication date: |
July 2011 |
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keywords: |
DEVS, Fuzzy Sets Theory, FIS, optimization models, iDEVS, DEVFIS |
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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. |
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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |