• DocumentCode
    3400698
  • Title

    Evolving artificial neural network structures: experimental results for biologically-inspired adaptive mutations

  • Author

    Miller, Damon A. ; Arguello, Rodrigo ; Greenwood, Garrison W.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Western Michigan Univ., Kalamazoo, MI, USA
  • Volume
    2
  • fYear
    2004
  • fDate
    19-23 June 2004
  • Firstpage
    2114
  • Abstract
    Previous work has suggested incorporating a biologically inspired mutation operator that reflects vertebrate neuron growth and death rates into an evolutionary algorithm for evolving artificial neural network structures. This paper further investigates this proposed approach by presenting experimental results for two classifier problems.
  • Keywords
    adaptive systems; evolutionary computation; neural nets; pattern classification; biologically-inspired adaptive mutations; classifier problems; evolutionary algorithm; evolving artificial neural network structures; mutation operator; neuron death rates; vertebrate neuron growth; Artificial neural networks; Biology computing; Computer networks; Evolutionary computation; Feedforward neural networks; Feedforward systems; Genetic mutations; Multi-layer neural network; Neural networks; Neurons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2004. CEC2004. Congress on
  • Print_ISBN
    0-7803-8515-2
  • Type

    conf

  • DOI
    10.1109/CEC.2004.1331157
  • Filename
    1331157
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3400698