DocumentCode :
3052443
Title :
Research on groundwater level prediction of Naoli river basin based on Elman wavelet neural networks
Author :
Peng Sheng-min ; Huang Jia-xin ; Fu Qiang
Author_Institution :
Coll. of Eng., Northeast Agric. Univ., Harbin, China
fYear :
2011
fDate :
26-28 July 2011
Firstpage :
5981
Lastpage :
5984
Abstract :
By combining Elman neural network with wavelet analysis, this paper establishes Elman-wavelet network model. The paper also presents the training process of Elman-wavelet network model, and applies the model to groundwater-level prediction of Naolihe basin. Numerical results derived demonstrate the model has high prediction accuracy, fast convergence and good prediction results.
Keywords :
geophysics computing; groundwater; learning (artificial intelligence); neural nets; rivers; wavelet transforms; China; Elman wavelet neural networks; Naoli river basin; Naolihe basin; groundwater level prediction; neural networktraining; Biological system modeling; Neurons; Numerical models; Predictive models; Training; Water resources; Wavelet analysis; Elman wavelet neural network; exploitation; groundwater;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Technology (ICMT), 2011 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-61284-771-9
Type :
conf
DOI :
10.1109/ICMT.2011.6003184
Filename :
6003184
Link To Document :
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