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dc.contributor.authorAsma, Senay
dc.contributor.authorSezer, Ahmet
dc.contributor.authorÖzdemir, Özer
dc.date.accessioned2019-10-20T09:31:16Z
dc.date.available2019-10-20T09:31:16Z
dc.date.issued2012
dc.identifier.issn0098-3004
dc.identifier.issn1873-7803
dc.identifier.urihttps://dx.doi.org/10.1016/j.cageo.2012.05.032
dc.identifier.urihttps://hdl.handle.net/11421/17650
dc.descriptionWOS: 000311656300025en_US
dc.description.abstractMultiple linear regression (MLR) and artificial neural network (ANN) models are used in the present work to describe the significant wave height off Goa, located in the west Indian coast. A comparison study was carried out with the purpose of verifying when the artificial neural network and multiple linear regression models are appropriate for prediction of the significant wave height. Discussions of advantages and disadvantages are given in different point of view for both the methods. Several meteorological factors are used during the analysis and the ones affecting more to the model are kept. We concluded that non-linear models with wind speed and wind gust at a previous time step and air pressure, water temperature and air temperature at the same time step yield to better significant wave height modelsen_US
dc.language.isoengen_US
dc.publisherPergamon-Elsevier Science LTDen_US
dc.relation.isversionof10.1016/j.cageo.2012.05.032en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSignificant Wave Heighten_US
dc.subjectArtificial Neural Networken_US
dc.subjectMultiple Regression Modelingen_US
dc.titleMLR and ANN models of significant wave height on the west coast of Indiaen_US
dc.typearticleen_US
dc.relation.journalComputers & Geosciencesen_US
dc.contributor.departmentAnadolu Üniversitesi, Fen Fakültesi, İstatistik Bölümüen_US
dc.identifier.volume49en_US
dc.identifier.startpage231en_US
dc.identifier.endpage237en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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