• DocumentCode
    1648215
  • Title

    Genetic algorithm based self-growing training for RBF neural networks

  • Author

    Bai, Yungei ; Zhang, L.

  • Author_Institution
    Sch. of Electron. & Electr. Eng., Leeds Univ., UK
  • Volume
    1
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    840
  • Lastpage
    845
  • Abstract
    Presents a RBF self-growing algorithm for training the RBFNN. The GA is employed to assist the search for the optimal RBFNN structure. The output layer weights are trained using a RLMS scheme with a dynamic learning rate
  • Keywords
    genetic algorithms; learning (artificial intelligence); least mean squares methods; radial basis function networks; RBF neural networks; RLMS scheme; dynamic learning rate; genetic algorithm based self-growing training; least mean square learning rule; optimal structure; output layer weights; radial basis function neural networks; search; training technique; Clustering algorithms; Genetic algorithms; Joining processes; Multi-layer neural network; Multilayer perceptrons; Neural networks; Neurons; Pattern classification; Radial basis function networks; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7278-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2002.1005583
  • Filename
    1005583
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1648215