Comparison of Levenberg-Marquardt and Bayesian Regularization Learning Algorithms for Daily Runoff Forecasting

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dc.contributor.authorBor, Asli
dc.contributor.authorOkan, Merve
dc.date.accessioned2026-02-08T15:04:50Z
dc.date.available2026-02-08T15:04:50Z
dc.date.issued2025
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractIn this study, Multilayer Perceptron (MLP) with Levenberg-Marquardt and Bayesian Regularization algorithms machine learning methods are compared for modeling of the rainfall-runoff process. For this purpose, daily flows were forecast using 5844 discharge data monitored between 1999 and 2015 of D21A001 Kırkgöze gauging station on the Karasu River operated by DSI. 6 scenarios were developed during the studies. Our findings indicate that the estimated capability of the Bayesian Regularization algorithm were close to with Levenberg-Marquardt algorithm for training and testing, respectively. This study shows that different network structures and data representing land features can improve prediction for longer lead times. We consider that the ANN model accurately depicted the Karasu flows, and that our study will serve as a guide for more research on flooding and water storage.
dc.identifier.doi10.38088/jise.1375510
dc.identifier.endpage77
dc.identifier.issn2602-4217
dc.identifier.issue1
dc.identifier.startpage62
dc.identifier.urihttps://doi.org/10.38088/jise.1375510
dc.identifier.urihttps://hdl.handle.net/20.500.12885/4231
dc.identifier.volume9
dc.language.isoen
dc.publisherBursa Teknik Üniversitesi
dc.relation.ispartofJournal of Innovative Science and Engineering
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_DergiPark_20260207
dc.subjectNumerical Modelization in Civil Engineering
dc.subjectİnşaat Mühendisliğinde Sayısal Modelleme [EN] Water Resources Engineering
dc.subjectSu Kaynakları Mühendisliği
dc.titleComparison of Levenberg-Marquardt and Bayesian Regularization Learning Algorithms for Daily Runoff Forecasting
dc.typeArticle

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