• DocumentCode
    478143
  • Title

    Streamflow Simulation with an Integrated Approach of Wavelet Analysis and Artificial Neural Networks

  • Author

    Ju, Qin ; Yu, Zhongbo ; Hao, Zhenchun ; She, Chao ; Ou, Gengxin ; Liu, Dedong

  • Author_Institution
    Center for Global Change & Water Cycle, Hohai Univ., Nanjing
  • Volume
    2
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    564
  • Lastpage
    569
  • Abstract
    A loose type of wavelet neural network (WNN) model which utilizes the merits of the wavelet analysis method and artificial neural network is presented in this paper. The WNN model was applied to simulate the daily streamflow in the upper area of Nangao Reservoir at Shanwei City. The simulated streamflows with the WNN model were also compared to these simulated with back-propagation (BP) neural networks model for evaluating the performance of the WNN model. The numerical experiment shows that the simulation results with the WNN model are more accurate than these simulated with the BP model. The results also indicate that this method is feasible and effective for hydrological forecasting.
  • Keywords
    backpropagation; flow simulation; geophysics computing; hydrological techniques; neural nets; wavelet transforms; artificial neural networks; back-propagation neural networks; hydrological forecasting; streamflow simulation; wavelet analysis; wavelet neural network; Analytical models; Artificial neural networks; Chaos; Computational modeling; Computer networks; Neural networks; Predictive models; Time series analysis; Water resources; Wavelet analysis; BP neural network; daily river flows; wavelet analysis; wavelet neural network model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2008. ICNC '08. Fourth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-0-7695-3304-9
  • Type

    conf

  • DOI
    10.1109/ICNC.2008.203
  • Filename
    4667058