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Cooperation between the Inference System and the Rule Base by Using Multiobjective Genetic Algorithms

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Hybrid Artificial Intelligence Systems (HAIS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5271))

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Abstract

This paper presents an evolutionary Multiobjective learning model achieving positive synergy between the Inference System and the Rule Base in order to obtain simpler and still accurate linguistic fuzzy models by learning fuzzy inference operators and applying rule selection. The Fuzzy Rule Based Systems obtained in this way, have a better trade-off between interpretability and accuracy in linguistic fuzzy modeling applications.

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Author information

Authors and Affiliations

  1. Information Technologies Department, University of Huelva, 21071, Huelva, Spain

    Antonio Márquez, Francisco Alfredo Márquez & Antonio Peregrín

Authors
  1. Antonio Márquez
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  2. Francisco Alfredo Márquez
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  3. Antonio Peregrín
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Editor information

Editors and Affiliations

  1. Escuela Politécnica Superior, GICAP Research Group, Universidad de Burgo, Calle Francisco de Vitoria S/N, Edifico C, Campus Vena, 09006, Burgos, Spain

    Emilio Corchado

  2. Center of Excellence for Quantifiable Quality of Service, Norwegian University of Science and Technology, 7491, Trondheim, Norway

    Ajith Abraham

  3. Department of Electrical and Computer Engineering, University of Alberta, Edmonton,, T6G 2V4, Alberta, Canada

    Witold Pedrycz

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© 2008 Springer-Verlag Berlin Heidelberg

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Márquez, A., Márquez, F.A., Peregrín, A. (2008). Cooperation between the Inference System and the Rule Base by Using Multiobjective Genetic Algorithms. In: Corchado, E., Abraham, A., Pedrycz, W. (eds) Hybrid Artificial Intelligence Systems. HAIS 2008. Lecture Notes in Computer Science(), vol 5271. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87656-4_91

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  • DOI: https://doi.org/10.1007/978-3-540-87656-4_91

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87655-7

  • Online ISBN: 978-3-540-87656-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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