• DocumentCode
    1636686
  • Title

    The fast neural network solution for problems based on slow genetic algorithm solutions

  • Author

    Wang, Yan ; Lu, Yilong

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
  • Volume
    2
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    1763
  • Lastpage
    1768
  • Abstract
    This paper presents a study of using radial basis function neural network, that is trained by a finite number of off-line slow genetic algorithm solutions, for infinite number of fast approximate solutions. This approach makes powerful yet slow genetic algorithm solutions possible for real time problems
  • Keywords
    approximation theory; genetic algorithms; radial basis function networks; fast approximate solutions; genetic algorithm solutions; neural network solution; radial basis function neural network; real time problems; Array signal processing; Feedforward neural networks; Genetic algorithms; Genetic engineering; Multi-layer neural network; Neural networks; Power engineering and energy; Radial basis function networks; Software design; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    0-7803-7282-4
  • Type

    conf

  • DOI
    10.1109/CEC.2002.1004509
  • Filename
    1004509
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1636686