Paul-Antoine Bisgambiglia

JDEVS: an implementation of a DEVS based formal framework for environmental modelling

The development of models using multiple modelling paradigms is necessary to formulate and study current problems in environmental science. To simplify the coupling of those models, a formal basis for a high-level specification of such models must be set up. In this paper, we propose a discrete event system specification (DEVS) based modelling framework as a formal basis in environmental modelling. The formal framework ensures that the models are reusable and interoperable components with well defined interfaces. Moreover, a wide variety of modelling paradigms can be expressed in the DEVS formalism. We also extend the modelling paradigms that can be expressed in the DEVS framework with two techniques: Feedback-DEVS for the specification of supervised-learning models and Vector-DEVS for the specification of models in vector space. JDEVS is the Java implementation of the framework. It enables discrete event, general purpose, object oriented, component based, GIS connected, collaborative, visual simulation model development and execution. A Feedback-DEVS neural-network model and a cellular infiltration model are described as experiments using JDEVS. Those models are later coupled to show the new modelling scenarios enabled by the use of a formal framework and the flexibility of the software.

A survey of modelling and simulation software frameworks using Discrete Event System Specification

Discrete Event System Specification is an extension of the Moore machine formalism which is used for modelling and analyzing general systems. This hierarchical and modular formalism is time event based and is able to represent any continuous, discrete or combined discrete and continuous systems. Since its introduction by B.P. Zeigler at the beginning of the eighties, most general modelling formalisms able to represent dynamic systems have been subsumed by DEVS. Meanwhile, the modelling and simulation (M&S) community has introduced various software frameworks supporting DEVS-based simulation analysis capability. DEVS has been used in many application domains and this paper will present a technical survey of the major DEVS implementations and software frameworks. We introduce a set of criteria in order to highlight the main features of each software tool, then we propose a table and discussion enabling a fast comparison of the presented frameworks. 1998 ACM Subject Classification I.6 Simulation and modeling

Fuzzy inference models for Discrete EVent systems

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.

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

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.

Fuzzy simulation for discrete events systems

The aim of our research is to develop a new method of taking into account the imperfect parameters in a discrete events modeling and simulation formalism. This article describes our approach to modeling and compares several methods for fuzzy simulations.

BFS-DEVS: A General DEVS-Based Formalism For Behavioral Fault Simulation

Discrete event modeling allows designing an easy-to-handle and reusable representation of a system but, in its classical form, only permits one simulation at a time for a system. Concurrent and Comparative Simulation (CCS) with Multi-List Propagation (MLP) appears to be an adapted solution, by providing a way to perform several simulations in a single execution run. Concurrent Fault Simulation (CFS) has been one of the first applications of the CCS. The main obstacles to a wide use of this technique are the high complexity of the concurrent simulation algorithms, along with the difficulty to integrate them in a simulation kernel. We focus in this paper on the CFS with MLP of systems described in the new BFS-DEVS formalism, which is an evolution of the original DEVS Simulator that integrates the CCS algorithm. The appli- cation is performed in the behavioral digital domain of systems described in the VHDL language.

iDEVS: New method to study inaccurate systems

Our recent research in the fields of modeling and simulation of complex systems, led us to study fuzzy systems. A system is fuzzy, because its parameters are inaccurate, or its behavior is uncertain. We propose in this paper to describe a new modeling method based on the association of DEVS formalism and the fuzzy sets theory. The combination of these two approaches we have permit to define a new method of inaccurate modeling. Our goal is to study systems with inaccurate parameters.

DEVS-Flou: a discrete events and fuzzy sets theory-based modeling environment

The objective of this article is to present a generic approach of multi-modeling and of simulation of complex systems. In order to take into account fuzzy or badly known parameters, we propose to define an approach allowing the addition of a technique based on the fuzzy sets theory, in an environment of multi-modeling JDEVS based on unifying formalism DEVS

A fuzzy approach of modeling evolutionary interfaces systems

The objective of this article is to present a theoretical approach of evolutionary interfaces object-oriented modeling. It is proposed to apply it to a wildland fire spread model that is multidisciplinary by essence. Our aim is to propose a decision support system to effectively and rapidly take into account complexity and uncertainties related to the factors influencing the fire spread.

Discrete events system simulation-based deFuzzification method

This article presents our approach to discrete event simulation for system with inaccurate parameters. For such systems, simulation runs according to events whose dates are known; but in fuzzy modeling, it may be that the date of the events are inaccurate. To solve this problem, we suggest using a method that converts a inaccurate value into accurate value. This method is incorporated into a modelling and simulation formalism.