Models-based Optimization Methods for the Specication of Fuzzy Inference Systems in Discrete EVent Simulation
نویسندگان
چکیده
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 signi cant 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 o ered by FIS: exibility, easy implementation, robustness... In this paper, we present the extension of Discrete EVent system Speci cation (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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