Chapter

Hybrid Artificial Intelligence Systems

Volume 6077 of the series Lecture Notes in Computer Science pp 1-8

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

  • Michel GonzálezAffiliated withCarnegie Mellon UniversityUniversidad Central “Marta Abreu” de Las Villas, CUBA
  • , Jorge CasillasAffiliated withCarnegie Mellon UniversityDept. Computer Science and Artificial Intelligence, University of Granada
  • , Carlos MorellAffiliated withCarnegie Mellon UniversityUniversidad Central “Marta Abreu” de Las Villas, CUBA

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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.