• DocumentCode
    423765
  • Title

    Ensemble algorithm of neural networks and its application

  • Author

    Liu, We ; Wang, Yuan ; Zhang, Bo-Feng ; Wu, Geng-feng

  • Author_Institution
    Sch. of Comput. Eng. & Sci., Shanghai Univ., China
  • Volume
    6
  • fYear
    2004
  • fDate
    26-29 Aug. 2004
  • Firstpage
    3464
  • Abstract
    Neural network ensemble is a very hot topic in both neural networks and machine learning communities (A. Sharkey, 1999). A new approach named BAGAEN is proposed, in which adaptive genetic algorithm and bootstrap algorithms are employed to increase the different degrees among individual RBF neural networks in order to enhance the generalization ability of a neural network system. The training set for individual RBF neural network is generated by the algorithm based on bootstrap and the result can be obtained by using majority voting method or simple averaging method. Experimental results show that BAGAEN has preferable performance in generating ensembles with strong generalization ability. Finally, BAGAEN is applied to predict the magnitude of earthquake.
  • Keywords
    genetic algorithms; learning (artificial intelligence); neural net architecture; radial basis function networks; RBF neural networks; adaptive genetic algorithm; bootstrap algorithms; machine learning; neural network ensemble; Application software; Bagging; Boosting; Computer networks; Earthquakes; Genetic algorithms; Machine learning; Machine learning algorithms; Neural networks; Voting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
  • Print_ISBN
    0-7803-8403-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2004.1380387
  • Filename
    1380387