SUSPENDED SEDIMENT LOAD PREDICTION IN RIVERS BY USING HEURISTIC REGRESSION AND HYBRID ARTIFICIAL INTELLIGENCE MODELS

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dc.authorid0000-0002-7553-9313en_US
dc.contributor.authorYımaz, Banu
dc.contributor.authorAras, Egemen
dc.contributor.authorKankal, Murat
dc.contributor.authorNacar, Sinan
dc.date.accessioned2021-03-20T20:09:26Z
dc.date.available2021-03-20T20:09:26Z
dc.date.issued2020
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, İnşaat Mühendisliği Bölümüen_US
dc.description.abstractAccurate prediction of amount of sediment load in rivers is extremely important for river hydraulics. The solution of the problem has been become complicated since the explanation of hydraulic phenomenon between the flow and the sediment on the river is dependent many parameters. The usage of different regression methods and artificial intelligence techniques allows the development of predictions as the traditional methods do not give enough accurate results. In this study, data of the flow and suspended sediment load (SSL) obtained from Karsikoy Gauging Station, located on Coruh River in the north-eastern of Turkey, modelled with different regression methods (multiple regression, multivariate adaptive regression splines) and artificial neural network (ANN) (ANN-back propagation, ANN teaching-learning-based optimization algorithm and ANN-artificial bee colony). When the results were evaluated, it was seen that the models of ANN method were close to each other and gave better results than the regression models. It is concluded that these models of ANN method can be used successfully in estimating the SSL.en_US
dc.identifier.endpage714en_US
dc.identifier.issn1304-7205
dc.identifier.issn1304-7191
dc.identifier.issue2en_US
dc.identifier.startpage703en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12885/415
dc.identifier.volume38en_US
dc.identifier.wosWOS:000545364300016en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.institutionauthorAras, Egemen
dc.language.isoenen_US
dc.publisherYildiz Technical Univen_US
dc.relation.ispartofSigma Journal Of Engineering And Natural Sciences-Sigma Muhendislik Ve Fen Bilimleri Dergisien_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial intelligenceen_US
dc.subjectCoruh river basinen_US
dc.subjectregression analysisen_US
dc.subjectriver hydraulicsen_US
dc.subjectsuspended sediment loaden_US
dc.titleSUSPENDED SEDIMENT LOAD PREDICTION IN RIVERS BY USING HEURISTIC REGRESSION AND HYBRID ARTIFICIAL INTELLIGENCE MODELSen_US
dc.typeArticleen_US

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