A Multimodel Approach for Complex Systems Modeling based on Classification Algorithms

Authors

  • Nesrine Elfelly Ecole Polytechnique de lille, Ecole Nationale d’Ingénieurs de Tunis -LARA Automatique (ENIT), Ecole Centrale de Lille (EC Lille) Laboratoire d’Automatique, Génie Informatique et Signal Ecole Centrale de Lille, Cité scientifique BP 48 59651 Villeneuve d’Ascq Cedex, France
  • Jean-Yves Dieulot Université des Sciences et Technologies de Lille (USTL), Ecole Polytechnique de lille, Ecole Nationale d’Ingénieurs de Tunis -LARA Automatique (ENIT), Ecole Centrale de Lille (EC Lille) Laboratoire d’Automatique, Génie Informatique et Signal Ecole Centrale de Lille, Cité scientifique BP 48 59651 Villeneuve d’Ascq Cedex, France
  • Mohamed Benrejeb Université des Sciences et Technologies de Lille (USTL), Ecole Polytechnique de lille, Ecole Nationale d’Ingénieurs de Tunis -LARA Automatique (ENIT), Ecole Centrale de Lille (EC Lille) Laboratoire d’Automatique, Génie Informatique et Signal Ecole Centrale de Lille, Cité scientifique BP 48 59651 Villeneuve d’Ascq Cedex, France
  • Pierre Borne Université des Sciences et Technologies de Lille (USTL), Ecole Polytechnique de lille, Ecole Nationale d’Ingénieurs de Tunis -LARA Automatique (ENIT), Ecole Centrale de Lille (EC Lille) Laboratoire d’Automatique, Génie Informatique et Signal Ecole Centrale de Lille, Cité scientifique BP 48 59651 Villeneuve d’Ascq Cedex, France

Keywords:

complex systems, multimodel, system modeling, classification

Abstract

In this paper, a new multimodel approach for complex systems modeling based on classification algorithms is presented. It requires firstly the determination of the model-base. For this, the number of models is selected via a neural network and a rival penalized competitive learning (RPCL), and the operating clusters are identified by using the fuzzy K-means algorithm. The obtained results are then exploited for the parametric identification of the models. The second step consists in validating the proposed model-base by using the adequate method of validity computation. Two examples are presented in this paper which show the efficiency of the proposed approach.

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Published

2014-09-16

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