Fuzz-iDEVS: towards a fuzzy toolbox for discrete event systems

Abstract

In this paper, we present a set of tools for the simulation of fuzzy systems. The described methods allow to take into account and to handle a lot of imperfect parameters for the studied systems. The methods developed are based on fuzzy logic and DEVS formalism. Their goal is to expand fields of application of simulation environments, and to foster interdisciplinary collaborations. At first, we have applied them to study the spread of forest fires. This application was developed in collaboration with the fire-fighters.

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

“…The theoretical approach and a rst application to dene real-time coecient of res spreading was proposed in [7]. The rst part of its implementation was presented in [12].…”

“…The DEVS formalism introduced by Zeigler [3] has been developed and upheld for over thirty years by an International community of researchers [17,16,7]. The work undertaken is part of the eort to develop an approach which will facilitate the modeling, simulation and validation phases of the study of complex systems.…”

“…We must think about adding an input port to the part of the FIS to be optimized, its aim is to replace the initial parameters for the optimized parameters. All these models come complete our library [7].…”

“…Our interest focuses on DEVS is formalism for modeling discrete event systems. Eorts were taken to adapt this formalism to dierent areas and situations [3,17,16,7] In this large niche, we look to the problem of fuzzy parameter systems.…”

“…Knowledge representation and the inclusion of imperfect knowledge is, in our view, a key step in an eort to optimally incorporate computational intelligence methods in a modeling and simulation framework [7]. We dene imperfect knowledge as: uncertain, there is a doubt about their validity; imprecise, it is dicult to quantify, inconsistent: there is inconsistencies in the data.…”