Population Learning Metaheuristic for Neural Network Training

  • Ireneusz Czarnowski
  • Piotr Jędrzejowicz
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 19)


Population based methods handle a population of individuals that evolves with the help of information exchange and self-improvement procedures. In this paper an application of a new metaheuristic called population learning algorithm (PLA) to ANN is investigated. The paper proposes several implementations of the PLA to training feed-forward artificial neural networks. The approach is validated by means of computational experiment in which PLA algorithm is used to train ANN solving a variety of benchmarking problems. Results of the experiment prove that PLA can be considered as a useful and effective tool for training ANN.


Initial Population Neural Network Training Wisconsin Breast Cancer Neural Network Training Algorithm Global Minimization Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Ireneusz Czarnowski
    • 1
  • Piotr Jędrzejowicz
    • 1
  1. 1.Department of Information SystemsGdynia Maritime UniversityGdyniaPoland

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