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Significant Wave Height Forecasting using GMDH Model

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Sajad Shahabi, Mohammad-Javad Khanjani, Masoud-reza Hessami Kermani
10.5120/ijca2016908129

Sajad Shahabi, Mohammad-Javad Khanjani and Masoud-reza Hessami Kermani. Article: Significant Wave Height Forecasting using GMDH Model. International Journal of Computer Applications 133(16):13-16, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Sajad Shahabi and Mohammad-Javad Khanjani and Masoud-reza Hessami Kermani},
	title = {Article: Significant Wave Height Forecasting using GMDH Model},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {133},
	number = {16},
	pages = {13-16},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Forecasting of significant wave height (SWH) is necessary for most of ocean engineering activities. Different models have been applied to forecast SWH at various lead times. Here, group method of data handling as a data learning machine method is used to forecast the SWH for next 3, 6 and 12. The SWH data are collected from station 41036 located in the North Atlantic Ocean. The model performance was evaluated using three different index including root mean square error (RMSE), coefficient of correlation (R) and index of agreement (Ia). The results shows that in short lead times, the predicted significant wave height mostly correlated to the observed significant wave height but in larger lead times this correlation decreased.

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Keywords

GMDH, lead time, significant wave height, time series.