SIFT-SS: An Advanced Steady-State Multi-Objective Genetic Fuzzy System

  • Michel González
  • Jorge Casillas
  • Carlos Morell
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6077)

Abstract

Nowadays, automatic learning of fuzzy rule-based systems is being addressed as a multi-objective optimization problem. A new research area of multi-objective genetic fuzzy systems (MOGFS) has capture the attention of the fuzzy community. Despite the good results obtained, most of existent MOGFS are based on a gross usage of the classic multi-objective algorithms. This paper takes an existent MOGFS and improves its convergence by modifying the underlying genetic algorithm. The new algorithm is tested in a set of real-world regression problems with successful results.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Michel González
    • 1
  • Jorge Casillas
    • 2
  • Carlos Morell
    • 1
  1. 1.Universidad Central “Marta Abreu” de Las Villas, CUBA 
  2. 2.Dept. Computer Science and Artificial IntelligenceUniversity of GranadaSpain

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