DocumentCode :
527794
Title :
LS-SVM forecast model of precipitation and runoff based on EMD
Author :
Ding, Zhihong ; Zhang, Jianwei ; Xie, Guoquan
Author_Institution :
Yellow River Inst. of Hydraulic Res., Zhengzhou, China
Volume :
4
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
1721
Lastpage :
1725
Abstract :
Through analyzing problem of Wavelet Transform, the annual precipitation series from 1956 to 2000 of the two sub-water resources regions of upper Lanzhou are decomposed into multiple time scale series with EMD method. The results show that the precipitation series have periods that about 3, 4~8, 11 and 22 years. A LS-SVM forecast model of precipitation and runoff based on EMD is established and then compared with the corresponding multivariable regression forecast model. It shows that, as a new and original signal processing method, Empirical Mode Decomposition, EMD, can be used as a tool to decompose hydrological time series into exact multiple time scale sub-series for finding their local change rule, and then to supply input variables with high quality and multiple levels to enhance model quality remarkably.
Keywords :
geophysics computing; precipitation; regression analysis; support vector machines; time series; wavelet transforms; weather forecasting; EMD method; LS-SVM forecast model; annual precipitation series; empirical mode decomposition; hydrological time series decomposition; multiple time scale series; multivariable regression forecast model; subwater resources regions; upper Lanzhou; wavelet transform; Analytical models; Computational modeling; Linear regression; Predictive models; Support vector machines; Time series analysis; Wavelet transforms; EMD; LS-SVM; forecast model; precipitation and runoff;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
Type :
conf
DOI :
10.1109/ICNC.2010.5584337
Filename :
5584337
Link To Document :
بازگشت