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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
