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Evolutionary Computation for Model and Feature Optimization

  • Lubica Benuskova
  • Nikola Kasabov
Chapter
  • 561 Downloads
Part of the Topics in Biomedical Engineering. International Book Series book series (ITBE)

Abstract

This chapter introduces the main principles of evolutionary computation (EC) and presents a methodology for using it to optimize the parameters and the set of features (e.g. genes, brain signals) in a computational model. Evolutionary computation (EC) methods adopt principles from the evolution in Nature (Darwin 1859). EC methods are used in Chaps. 7 and 8 of the book to optimize gene interaction networks as part of a CNGM.

Keywords

Genetic Algorithm Evolutionary Computation Travel Salesman Problem Lifelong Learning Feature Optimization 
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 Science + Business Media, LLC 2007

Authors and Affiliations

  • Lubica Benuskova
    • 1
  • Nikola Kasabov
    • 1
  1. 1.Knowledge Engineering and Discovery Research InstituteAUTAucklandNew Zealand

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