Ship waste forecasting at the Botas LNG Port using artificial neural networks

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dc.contributor.authorSatir T.
dc.contributor.authorDemir H.
dc.contributor.authorAlkan G.B.
dc.contributor.authorUcan O.N.
dc.contributor.authorBayat C.
dc.date.accessioned2024-03-13T10:01:30Z
dc.date.available2024-03-13T10:01:30Z
dc.date.issued2008
dc.departmentİstanbul Beykent Üniversitesien_US
dc.description.abstractCargo and passenger vessels are required to give their waste to reception facilities when at port, and due to new regulations Turkish ports need to establish or reconstruct these facilities. It is thus very important for ports to be able to predict the quantity of waste. In this study, the authors use Artificial Neural Networks (ANNs) to model four years of data on the reception of ship's waste at the Botas LNG Port in Marmara Ereglisi, Turkey. Satisfactory results are obtained by the ANN outputs, and confirmed by classical approaches. This ANN forecasting model can be used by waste management companies to plan new ports.en_US
dc.identifier.endpage2070en_US
dc.identifier.issn1018-4619
dc.identifier.issue12 Aen_US
dc.identifier.scopus2-s2.0-61949163940en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage2064en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12662/3232
dc.identifier.volume17en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofFresenius Environmental Bulletinen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectForecastingen_US
dc.subjectGarbageen_US
dc.subjectMarine pollutionen_US
dc.subjectNeural networksen_US
dc.subjectWasteen_US
dc.subjectWaveletsen_US
dc.titleShip waste forecasting at the Botas LNG Port using artificial neural networksen_US
dc.typeArticleen_US

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