DocumentCode :
3022641
Title :
A New Method of Periods´ Identification in Hydrologic Series Based on EEMD
Author :
Sang, Yan-Fang ; Wang, Dong ; Wu, Ji-Chun ; Zhu, Qing-Ping ; Wang, Ling
Author_Institution :
Dept. of Hydrosciences, Nanjing Univ., Nanjing, China
Volume :
4
fYear :
2009
fDate :
7-8 Nov. 2009
Firstpage :
269
Lastpage :
273
Abstract :
Identification of dominant periods is a very important but difficult task in hydrologic time series data analysis. In this paper, for improving the results of periods´ identification, a new method, called EEMD-MESA (ensemble empirical mode decomposition-maximum entropy spectral analysis), has been proposed, whose main idea is identifying the main intrinsic mode functions (MIMFs) in hydrologic series firstly, and then by using MESA to identify periods in each MIMFs, all periods in the hydrologic series can be gotten finally. By applying to an observed runoff series, advantages of the new method have been verified. Analyses results show that EEMD-MESA is as better as MSSA but much better than other methods (FFT and MESA); While compared with MSSA, EEMD-MESA is more convenient and time-saving. Therefore, the EEMD-MESA method would be more applicable to practical hydrologic works.
Keywords :
data analysis; geophysical signal processing; hydrological techniques; maximum entropy methods; spectral analysis; time series; ensemble empirical mode decomposition-maximum entropy spectral analysis; hydrologic time series data analysis; main intrinsic mode function; Data analysis; Data engineering; Entropy; Hydrology; Independent component analysis; Noise reduction; Spectral analysis; Time series analysis; Water resources; Wavelet analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
Type :
conf
DOI :
10.1109/AICI.2009.236
Filename :
5376358
Link To Document :
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