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
Link To Document :
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