• DocumentCode
    3284570
  • Title

    A Modular Neural Networks ensembling method based on fuzzy decision-making

  • Author

    Bo, Ying-Chun ; Qiao, Jun-fei ; Yang, Gang

  • Author_Institution
    Coll. of Electron. & Control Eng., Beijing Univ. of Technol., Beijing, China
  • fYear
    2011
  • fDate
    15-17 April 2011
  • Firstpage
    1030
  • Lastpage
    1034
  • Abstract
    This paper integrates the ideas of "divide and conquer" and "put the heads together", and proposes a method of selecting sub-networks on-line based on fuzzy decision making. For a given input, this method calculates the distances between the input and the centers of sub-networks firstly, and then obtains the fuzzy member degree based on distance measure, finally realizes on-line sub-networks selection by fuzzy decision-making. The group of selected sub-networks varies with different inputs. It ensembles multi sub-networks by linear method. The weights of sub-networks are optimized by reconstructing the sample space. The simulation results suggest that this method can improve the precision and generalization ability effectively.
  • Keywords
    decision making; divide and conquer methods; fuzzy set theory; neural nets; optimisation; distance measure; divide and conquer method; fuzzy decision making; fuzzy member degree; generalization ability; linear method; modular neural network ensembling method; online subnetwork selection; precision ability; put the head together method; sample space reconstruction; subnetwork weight optimization; Artificial neural networks; Decision making; Mathematical model; Multi-layer neural network; Noise; Optimization; Training; Fuzzy Decision-making; Modular Neural Networks; Weights Optimization; self-adaptive integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Information and Control Engineering (ICEICE), 2011 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-8036-4
  • Type

    conf

  • DOI
    10.1109/ICEICE.2011.5777823
  • Filename
    5777823