Modelling the Rainfall-Runoff Data of Susurluk Basin

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dc.contributor.authorDorum, Atila
dc.contributor.authorYarar, Alpaslan
dc.contributor.authorSevimli, M. Faik
dc.contributor.authorOnüçyıdız, Mustafa
dc.date.accessioned2020-03-26T18:04:42Z
dc.date.available2020-03-26T18:04:42Z
dc.date.issued2010
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn this study, rainfall runoff relationship was tried to be set up by using Artificial Neural Networks (ANN) and Adaptive Neuro Fuzzy Interference Systems (ANFIS) models at Flow Observation Stations (FOS) on seven streams where runoff measurement has been made for long years in Susurluk Basin. A part of runoff data was used for training of ANN and ANFIS models and the other part was used to test the performance of the models. The performance comparison of the models was made with decisiveness coefficient (R(2)) and Root Mean Squared Errors (RMSE) values. In addition to this, a comparison of ANN and ANFIS with traditional methods was made by setting up Multi-regressional (MR) model. Except some stations, acceptable results such as R(2) value for ANN model and R(2) value for ANFIS model were obtained as 0.7587 and 0.8005, respectively. The high values of predicted errors, belonging to peak values at stations where multi variable flow is seen, affected R(2) and RMSE values negatively.en_US
dc.identifier.citationDorum, A., Yarar, A., Sevimli, M. F., Onüçyıdız, M., (2010). Modelling the Rainfall-Runoff Data of Susurluk Basin. Expert Systems with Applications, 37(9), 6587-6593. doi: org/10.1016/j.eswa.2010.02.127.
dc.identifier.doi10.1016/j.eswa.2010.02.127en_US
dc.identifier.endpage6593en_US
dc.identifier.issn0957-4174en_US
dc.identifier.issue9en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage6587en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.eswa.2010.02.127
dc.identifier.urihttps://hdl.handle.net/20.500.12395/25078
dc.identifier.volume37en_US
dc.identifier.wosWOS:000278424600054en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorYarar, Alpaslan
dc.institutionauthorSevimli, M. Faik
dc.institutionauthorOnüçyıdız, Mustafa
dc.language.isoenen_US
dc.publisherPERGAMON-ELSEVIER SCIENCE LTDen_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectModelling of rainfall-runoffen_US
dc.subjectArtificial Neural Networksen_US
dc.subjectNeuro fuzzyen_US
dc.subjectSusurluk Basinen_US
dc.titleModelling the Rainfall-Runoff Data of Susurluk Basinen_US
dc.typeArticleen_US

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