Predicting sea level variations with artificial neural networks at Hillarys Boat Harbour, Western Australia

In the present study, the artificial intelligence meshless methodology of neural networks was used to predict hourly sea level variations for the following 24 hours, as well as for half-daily, daily, 5-daily and 10-daily mean sea levels. The methodology is site specific; therefore, as an example, th...

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Main Authors: Makarynskyy, Oleg, Makarynska, D., Kuhn, Michael, Featherstone, Will
Format: Journal Article
Published: Elsevier 2004
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/43320
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author Makarynskyy, Oleg
Makarynska, D.
Kuhn, Michael
Featherstone, Will
author_facet Makarynskyy, Oleg
Makarynska, D.
Kuhn, Michael
Featherstone, Will
author_sort Makarynskyy, Oleg
building Curtin Institutional Repository
collection Online Access
description In the present study, the artificial intelligence meshless methodology of neural networks was used to predict hourly sea level variations for the following 24 hours, as well as for half-daily, daily, 5-daily and 10-daily mean sea levels. The methodology is site specific; therefore, as an example, the measurements from a single tide gauge at Hillarys Boat Harbour, Western Australia, for the period December 1991-December 2002 were used to train and to validate the employed neural networks. The results obtained show the feasibility of the neural sea level forecasts in terms of the correlation coefficient (0.7-0.9), root mean square error (about 10% of tidal range) and scatter index (0.1-0.2).
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institution Curtin University Malaysia
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last_indexed 2025-11-14T09:15:42Z
publishDate 2004
publisher Elsevier
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spelling curtin-20.500.11937-433202019-02-19T05:35:22Z Predicting sea level variations with artificial neural networks at Hillarys Boat Harbour, Western Australia Makarynskyy, Oleg Makarynska, D. Kuhn, Michael Featherstone, Will sea level variations - tide gauge - artificial neural networks - forecast - Western Australian coast In the present study, the artificial intelligence meshless methodology of neural networks was used to predict hourly sea level variations for the following 24 hours, as well as for half-daily, daily, 5-daily and 10-daily mean sea levels. The methodology is site specific; therefore, as an example, the measurements from a single tide gauge at Hillarys Boat Harbour, Western Australia, for the period December 1991-December 2002 were used to train and to validate the employed neural networks. The results obtained show the feasibility of the neural sea level forecasts in terms of the correlation coefficient (0.7-0.9), root mean square error (about 10% of tidal range) and scatter index (0.1-0.2). 2004 Journal Article http://hdl.handle.net/20.500.11937/43320 10.1016/j.ecss.2004.06.004 Elsevier fulltext
spellingShingle sea level variations - tide gauge - artificial neural networks - forecast - Western Australian coast
Makarynskyy, Oleg
Makarynska, D.
Kuhn, Michael
Featherstone, Will
Predicting sea level variations with artificial neural networks at Hillarys Boat Harbour, Western Australia
title Predicting sea level variations with artificial neural networks at Hillarys Boat Harbour, Western Australia
title_full Predicting sea level variations with artificial neural networks at Hillarys Boat Harbour, Western Australia
title_fullStr Predicting sea level variations with artificial neural networks at Hillarys Boat Harbour, Western Australia
title_full_unstemmed Predicting sea level variations with artificial neural networks at Hillarys Boat Harbour, Western Australia
title_short Predicting sea level variations with artificial neural networks at Hillarys Boat Harbour, Western Australia
title_sort predicting sea level variations with artificial neural networks at hillarys boat harbour, western australia
topic sea level variations - tide gauge - artificial neural networks - forecast - Western Australian coast
url http://hdl.handle.net/20.500.11937/43320