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You are here : eLibrary : IAHR World Congress Proceedings : 36th Congress - The Hague (2015) ALL CONTENT : Water engineering : Modelling of significant wave height using wavelet and genetic programming
Modelling of significant wave height using wavelet and genetic programming
Author : SAJAD SHAHABI(1) & MOHAMMAD-JAVAD KHANJANI(2)
Accurate modelling of significant wave height (SWH) is an essential issue for most of the ocean and coastal operations.
Traditional models are basically linear and assume that the data are stationary. Some models based on artificial neural
network (ANN) has been developed and employed for SWH modelling (Tsai et al., 2002; Markarynsky et al., 2005; Londhe
and Panchang, 2006). For some limitation of ANN, some other approaches such as genetic programming (GP) which is
evolutionary computing method has been presented and developed (Gaur and Deo, 2008). In spite of advantages of the
ANN and GP methods for SWH modelling, there is a limitation when signal are highly nonstationary. To cope with this
problem, some researchers hybridized wavelet technique with other methods (Nourani et al., 2014; Deka and Prahlada,
2012). The hybrid wavelet-GP (namely WGP) model was employed to rainfall-runoff modelling and drought forecasting
(Nourani et al., 2012; Danandeh Mehr et al., 2014). In this paper, a WGP model was employed to forecasting of SWH in
the west of North Atlantic Ocean.
File Size : 407,678 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 36th Congress - The Hague (2015) ALL CONTENT
Article : Water engineering
Date Published : 26/08/2015
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