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Designing Radial Basis Function Neural Networks with Meta-Evolutionary Algorithms: The Effect of Chromosome Codification

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Book cover Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living (IWANN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5518))

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Abstract

In this paper a study of two approaches of a meta-algorithm, Meta_CHC_RBF, is presented. The main goal of this algorithm is to automatically design Radial Basis Function Networks (RBFNs) finding a suitable configuration of parameters (automatically adapted to every problem) necessary for the algorithm EvRBF, an evolutionary algorithm for the automatic design of asymmetric RBFNs. The principal difference between two proposals is the type of codification, in the fist one, the meta-algorithm uses binary codification, while in the second one, it implements real codification; affecting this influence of the codification kind in the carried out experimentation. Finally, results show that the first approach yields good marks reducing the computation time, with respect the second one.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Sciences, Campus Las Lagunillas s/n, 23071, Jaen, Spain

    Elisabet Parras-Gutierrez, Victor M. Rivas & M. Jose del Jesus

  2. Department of Computer Architecture and Technology, CITIC-UGR, C/Periodista Daniel Saucedo s/n, 18071, Granada, Spain

    Juan J. Merelo

Authors
  1. Elisabet Parras-Gutierrez
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  2. Victor M. Rivas
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  3. M. Jose del Jesus
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  4. Juan J. Merelo
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Editor information

Editors and Affiliations

  1. Graduate School of Engineering, Osaka Prefecture University, Osaka, Japan

    Sigeru Omatu

  2. Department of Informatics / CCTC, University of Minho, Braga, Portugal

    Miguel P. Rocha

  3. MAmI Research Lab, University of Castilla-La Mancha,, Ciudad Real, Spain

    José Bravo

  4. Department of Informatics, University of Vigo, Ourense, Spain

    Florentino Fernández

  5. Grupo de Investigación GICAP, Área de Lenguajes Higher Polytechnic School, Universidad de Burgos, Burgos, Spain

    Emilio Corchado

  6. Higher Polytechnic School, University of Burgos, Burgos, Spain

    Andrés Bustillo

  7. Department of Informatics, University of Salamanca, Salamanca, Spain

    Juan M. Corchado

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© 2009 Springer-Verlag Berlin Heidelberg

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Parras-Gutierrez, E., Rivas, V.M., del Jesus, M.J., Merelo, J.J. (2009). Designing Radial Basis Function Neural Networks with Meta-Evolutionary Algorithms: The Effect of Chromosome Codification. In: Omatu, S., et al. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. IWANN 2009. Lecture Notes in Computer Science, vol 5518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02481-8_6

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  • DOI: https://doi.org/10.1007/978-3-642-02481-8_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02480-1

  • Online ISBN: 978-3-642-02481-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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