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Rbf Centers Initialization Using Fuzzy Clustering Technique For Function Approximation Problems

Author

Listed:
  • Guillén, A.
  • Rojas, I.
  • González, J.
  • Pomares, H.
  • Herrera, L.J.

    (University of Granada)

Abstract

In this paper, a new algorithm for RBF centers initialization for functional approximation problems is proposed. The design of the algorithm is inspired in previous clustering algorithms but adding some features to adapt the algorithm to the characteristics of our problem. We compare the results provided by our new algorithm with the results provided by the algorithms it is based on.

Suggested Citation

  • Guillén, A. & Rojas, I. & González, J. & Pomares, H. & Herrera, L.J., 2005. "Rbf Centers Initialization Using Fuzzy Clustering Technique For Function Approximation Problems," Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 0(2), pages 27-44, November.
  • Handle: RePEc:fzy:fuzeco:v:x:y:2005:i:2:p:27-44
    as

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    More about this item

    Keywords

    Neural networks; radial basis functions; function approximation; clustering;

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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