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dc.contributor.authorBayındır, Cihanen_US
dc.date.accessioned2023-01-05T15:18:02Z
dc.date.available2023-01-05T15:18:02Z
dc.date.issued2023-01
dc.identifier.citationBayındır, C. (2023). Predicting the ocean currents using deep learning. TWMS Journal Of Applied And Engineering Mathematics, 13(1), 373-385.en_US
dc.identifier.issn2146-1147en_US
dc.identifier.issn2587-1013en_US
dc.identifier.urihttp://belgelik.isikun.edu.tr/xmlui/handle/iubelgelik/5229
dc.identifier.urihttp://jaem.isikun.edu.tr/web/index.php/current/118-vol13no1/971
dc.description.abstractIn this paper, we analyze the predictability of the ocean currents using deep learning. More specifically, we apply the Long Short Term Memory (LSTM) deep learning network to a data set collected by the National Oceanic and Atmospheric Administration (NOAA) in Massachusetts Bay between November 2002-February 2003. We show that the current speed in two horizontal directions, namely u and v, can be predicted using the LSTM. We discuss the effect of training data set on the prediction error and on the spectral properties of predictions. Depending on the temporal or the spatial resolution of the data, the prediction times and distances can vary, and in some cases, they can be very beneficial for the prediction of the ocean current parameters. Our results can find many important applications including but are not limited to predicting the statistics and characteristics of tidal energy variation, controlling the current induced vibrations of marine structures and estimation of the wave blocking point by the chaotic oceanic current and circulation.en_US
dc.language.isoenen_US
dc.publisherIşık University Pressen_US
dc.relation.ispartofTWMS Journal Of Applied And Engineering Mathematicsen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectOceanic current and circulationsen_US
dc.subjectDeep learningen_US
dc.subjectLong short term memoryen_US
dc.subjectPredictability of oceanic circulationsen_US
dc.subjectSpectral properties of oceanic currenten_US
dc.titlePredicting the ocean currents using deep learningen_US
dc.typeArticleen_US
dc.description.versionPublisher's Versionen_US
dc.identifier.volume13
dc.identifier.issue1
dc.identifier.startpage373
dc.identifier.endpage385
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Başka Kurum Yazarıen_US
dc.indekslendigikaynakEmerging Sources Citation Index (ESCI)en_US
dc.indekslendigikaynakMathScineten_US
dc.indekslendigikaynakScopusen_US


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