DocumentCode :
1586810
Title :
Hydrologic Simulations with Artificial Neural Networks
Author :
Ju, Qin ; Yu, Zhongbo ; Hao, Zhenchun ; Zhu, Changjun ; Liu, Dedong
Author_Institution :
Hohai Univ., Nanjing
Volume :
2
fYear :
2007
Firstpage :
22
Lastpage :
27
Abstract :
A back-propagation (BP) neural networks model was used for simulating daily streamflows in the upper area of Nangao Reservoir at Shanwei City, Guangdong Province, China. Approaches and techniques of applying the BP model in runoff simulation are presented in this paper. A comparison of the BP model to the Xinanjiang model was also conducted to evaluate the performance of the BP model. The simulated results indicate a satisfactory performance in the streamflow forecasting with the BP model. The study concludes that the BP model has the high practicability and good accuracy for describing complex nonlinear hydrologic processes.
Keywords :
backpropagation; hydrological techniques; neural nets; reservoirs; Nangao reservoir; artificial neural network; backpropagation; hydrologic simulation; streamflow forecasting; Artificial neural networks; Biological system modeling; Computational modeling; Hydrologic measurements; Hydrology; Neural networks; Neurons; Power system modeling; Predictive models; Reservoirs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
Type :
conf
DOI :
10.1109/ICNC.2007.424
Filename :
4344309
Link To Document :
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