Hybrid Evolutionary Algorithm with Product-Unit Neural Networks for Classification

  • Francisco J. Martínez-Estudillo
  • César Hervás-Martínez
  • Alfonso C. Martínez-Estudillo
  • Pedro A. Gutiérrez-Peña
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4507)


In this paper we propose a classification method based on a special class of feed-forward neural network, namely product-unit neural networks, and on a dynamic version of a hybrid evolutionary neural network algorithm. The method combines an evolutionary algorithm, a clustering process, and a local search procedure, where the clustering process and the local search are only applied at specific stages of the evolutionary process. Our results with the product-unit models and the evolutionary approach show a very interesting performance in terms of classification accuracy, yielding a state-of-the-art performance.


Classification Product-Unit Neural Networks Evolutionary algorithms 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Francisco J. Martínez-Estudillo
    • 1
  • César Hervás-Martínez
    • 2
  • Alfonso C. Martínez-Estudillo
    • 1
  • Pedro A. Gutiérrez-Peña
    • 2
  1. 1.Department of Management and Quantitative Methods, ETEASpain
  2. 2.Department of Computing and Numerical Analysis of the University of CórdobaSpain

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