• DocumentCode
    2628995
  • Title

    Research of Wavelet Neural Network Model Based on Extenics

  • Author

    Wang, Hong ; Yu, Yongquan ; Zhu, Xiaoyuan

  • Author_Institution
    Guang Dong Univ. of Technol., Guangzhou
  • fYear
    2007
  • fDate
    21-23 Nov. 2007
  • Firstpage
    2024
  • Lastpage
    2029
  • Abstract
    In order to conquer the disadvantage of the traditional wavelet neural networks (WNN), the paper presents WNN model which is based on extenics. The model uses the feature number of matter element to determine the volume of importation of neuron number, makes sure the number of output neurons based on identification the type number needed, and makes a correct judgment about the neurons inhibit or activation. It optimizes the structure design of wavelet neural network. Then there is an experiment about the weather prediction using the new model. Experimental results show that the new model has better convergence and accuracy.
  • Keywords
    feedforward neural nets; wavelet transforms; weather forecasting; extenics theory; matter element theory; neuron number; wavelet neural network model; weather prediction; Artificial neural networks; Computer networks; Convergence; Design optimization; Feedforward neural networks; Information technology; Neural networks; Neurons; Set theory; Weather forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Convergence Information Technology, 2007. International Conference on
  • Conference_Location
    Gyeongju
  • Print_ISBN
    0-7695-3038-9
  • Type

    conf

  • DOI
    10.1109/ICCIT.2007.21
  • Filename
    4420550