DocumentCode :
527845
Title :
Study On tide prediction method based On LS-Support Vector Machines
Author :
He Shijun ; Zhou Wenjun ; Zhou Ruyan
Author_Institution :
Coll. of Inf., Shanghai Ocean Univ., Shanghai, China
Volume :
4
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
1869
Lastpage :
1872
Abstract :
The paper analyses the limited of tide prediction based on harmonic analysis method and BP neural network method. According to celestial motion law and weather or other non-periodic factors effect, the author designs a tide prediction method based on Least Square-Support Vector Machines (LS-SVM). This method preferably carries out the tide prediction which influenced by non-cyclical factors. Compared with harmonic analysis method and BP neural network method, this prediction method has faster modeling speed, higher prediction precision and stronger generalization ability.
Keywords :
backpropagation; geophysics computing; least squares approximations; neural nets; oceanographic techniques; support vector machines; tides; BP neural network method; celestial motion law; harmonic analysis method; least square-support vector machines; tide prediction method; Artificial neural networks; Azimuth; Earth; Kernel; Moon; Support vector machines; Tides; LS-SVM; celestial motion law; non-periodic factors; tidal prediction;
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.2010.5584609
Filename :
5584609
Link To Document :
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