• DocumentCode
    466520
  • Title

    Neural Network Topological Evolvement

  • Author

    Zhongda, Yuan ; Zhen, Ye

  • Author_Institution
    Dept. of Comput. Sci., Tsinghua Univ., Beijing
  • Volume
    1
  • fYear
    2006
  • fDate
    4-6 Oct. 2006
  • Firstpage
    408
  • Lastpage
    411
  • Abstract
    In order to obtain instance response from evolving neural networks, we separate the evolving procedure and the output procedure in the traditional GA approach, and make them simultaneously. Thanks to the support from database system, this modified GA has three characteristics, namely serialized storage, persistent evolving and instance response to end user´s request. In our experiment, this approach shows off better performance over the conventional strategy
  • Keywords
    data mining; genetic algorithms; neural nets; data mining; genetic algorithm; neural network topological evolvement; serialized storage; Application software; Computer science; Data mining; Database systems; Electronic mail; Genetics; Multi-layer neural network; Neural networks; Neurons; Systems engineering and theory; Data Mining; Genetic Algorism; Neural Network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Engineering in Systems Applications, IMACS Multiconference on
  • Conference_Location
    Beijing
  • Print_ISBN
    7-302-13922-9
  • Electronic_ISBN
    7-900718-14-1
  • Type

    conf

  • DOI
    10.1109/CESA.2006.4281687
  • Filename
    4281687