• DocumentCode
    2729566
  • Title

    A genetic algorithm based neural-tuned neural network

  • Author

    Ling, S.H. ; Lam, H.K. ; Leung, Frank H. F. ; Lee, YS

  • Author_Institution
    Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., Kowloon, China
  • Volume
    3
  • fYear
    2003
  • fDate
    2-6 Nov. 2003
  • Firstpage
    2423
  • Abstract
    This paper presents a neural-tuned neural network, which is trained by genetic algorithm (GA). The neural-tuned neural network consists of a neural network and a modified neural network. In the modified neural network, a neuron model with two activation functions is introduced. Some parameters of these activation functions is tuned by neural network. The proposed network structure can increase the search space of the network and gives better performance than traditional feedforward neural networks. Some application examples are given to illustrate the merits of the proposed network.
  • Keywords
    genetic algorithms; multilayer perceptrons; dynamic activation function; feedforward neural networks; genetic algorithm; neural-tuned neural network; pattern recognition; static activation function; sunspot forecasting; Control system synthesis; Feedforward neural networks; Feedforward systems; Genetic algorithms; Modeling; Multi-layer neural network; Neural networks; Neurons; Pattern recognition; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, 2003. IECON '03. The 29th Annual Conference of the IEEE
  • Print_ISBN
    0-7803-7906-3
  • Type

    conf

  • DOI
    10.1109/IECON.2003.1280624
  • Filename
    1280624