Prediction of the wave power in the Black Sea based on wind speed using artificial neural networks
The paper proposes a prediction methodology for the significant wave height (and implicitly the wave power), based on the artificial neural networks. The proposed approach takes as input data the wind speed values recorded for different time periods. The prediction of significant wave height is usef...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2018-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://doi.org/10.1051/e3sconf/20185101006 |
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doaj-250c53db0ea344d3ac41b46f5c2ba8122021-03-02T10:58:40ZengEDP SciencesE3S Web of Conferences2267-12422018-01-01510100610.1051/e3sconf/20185101006e3sconf_icacer2018_01006Prediction of the wave power in the Black Sea based on wind speed using artificial neural networksCiortan SorinRusu EugenThe paper proposes a prediction methodology for the significant wave height (and implicitly the wave power), based on the artificial neural networks. The proposed approach takes as input data the wind speed values recorded for different time periods. The prediction of significant wave height is useful both for assessment of wave energy as also for marine equipment design and navigation. The data used cover the time interval 1999 to 2007 and it was measured on Gloria drilling unit, which operates in the Romanian nearshore of the Black Sea at about 500 meters depth.https://doi.org/10.1051/e3sconf/20185101006 |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Ciortan Sorin Rusu Eugen |
| spellingShingle |
Ciortan Sorin Rusu Eugen Prediction of the wave power in the Black Sea based on wind speed using artificial neural networks E3S Web of Conferences |
| author_facet |
Ciortan Sorin Rusu Eugen |
| author_sort |
Ciortan Sorin |
| title |
Prediction of the wave power in the Black Sea based on wind speed using artificial neural networks |
| title_short |
Prediction of the wave power in the Black Sea based on wind speed using artificial neural networks |
| title_full |
Prediction of the wave power in the Black Sea based on wind speed using artificial neural networks |
| title_fullStr |
Prediction of the wave power in the Black Sea based on wind speed using artificial neural networks |
| title_full_unstemmed |
Prediction of the wave power in the Black Sea based on wind speed using artificial neural networks |
| title_sort |
prediction of the wave power in the black sea based on wind speed using artificial neural networks |
| publisher |
EDP Sciences |
| series |
E3S Web of Conferences |
| issn |
2267-1242 |
| publishDate |
2018-01-01 |
| description |
The paper proposes a prediction methodology for the significant wave height (and implicitly the wave power), based on the artificial neural networks. The proposed approach takes as input data the wind speed values recorded for different time periods. The prediction of significant wave height is useful both for assessment of wave energy as also for marine equipment design and navigation. The data used cover the time interval 1999 to 2007 and it was measured on Gloria drilling unit, which operates in the Romanian nearshore of the Black Sea at about 500 meters depth. |
| url |
https://doi.org/10.1051/e3sconf/20185101006 |
| work_keys_str_mv |
AT ciortansorin predictionofthewavepowerintheblackseabasedonwindspeedusingartificialneuralnetworks AT rusueugen predictionofthewavepowerintheblackseabasedonwindspeedusingartificialneuralnetworks |
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1724235736012554240 |