• DocumentCode
    1747223
  • Title

    Research on fast training algorithm for recurrent neural network

  • Author

    Gong, Dunwei ; Xu, Shifan ; Sun, Xiaoyan

  • Author_Institution
    Coll. of Inf. & Electr. Eng., China Univ. of Mining & Technol., Jiangsu, China
  • Volume
    1
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    446
  • Abstract
    In this paper, strategy on training recurrent neural networks based on genetic algorithms is expounded, which includes several key issues in designing a genetic algorithm, choice of running parameters and diagram of training method. Then forecasting nonlinear system using recurrent neural network is present. Simulation shows the method is effective
  • Keywords
    genetic algorithms; learning (artificial intelligence); recurrent neural nets; fast training algorithm; genetic algorithms; nonlinear system forecasting; recurrent neural network; running parameters; Algorithm design and analysis; Control system synthesis; Educational institutions; Genetic algorithms; Genetic mutations; Neurons; Nonlinear control systems; Nonlinear systems; Recurrent neural networks; Sun;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics, 2001. Proceedings. ISIE 2001. IEEE International Symposium on
  • Conference_Location
    Pusan
  • Print_ISBN
    0-7803-7090-2
  • Type

    conf

  • DOI
    10.1109/ISIE.2001.931831
  • Filename
    931831
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1747223