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

  • Michel González
  • Jorge Casillas
  • Carlos Morell
Conference paper

DOI: 10.1007/978-3-642-13803-4_1

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6077)
Cite this paper as:
González M., Casillas J., Morell C. (2010) SIFT-SS: An Advanced Steady-State Multi-Objective Genetic Fuzzy System. In: Corchado E., Graña Romay M., Manhaes Savio A. (eds) Hybrid Artificial Intelligence Systems. HAIS 2010. Lecture Notes in Computer Science, vol 6077. Springer, Berlin, Heidelberg

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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