Comparison of Levenberg-Marquardt and Bayesian Regularization Learning Algorithms for Daily Runoff Forecasting
In 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 D21A0...
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| Format: | Article |
| Language: | English |
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Bursa Technical University
2025-06-01
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| Series: | Journal of Innovative Science and Engineering |
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| Online Access: | http://jise.btu.edu.tr/en/download/article-file/3472764 |
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| author | Aslı BOR Merve OKAN |
| author_facet | Aslı BOR Merve OKAN |
| author_sort | Aslı BOR |
| collection | DOAJ |
| description | In 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.
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| format | Article |
| id | doaj-art-d31e6fc1374847dabb401de3c747ca94 |
| institution | Kabale University |
| issn | 2602-4217 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Bursa Technical University |
| record_format | Article |
| series | Journal of Innovative Science and Engineering |
| spelling | doaj-art-d31e6fc1374847dabb401de3c747ca942025-08-20T03:58:49ZengBursa Technical UniversityJournal of Innovative Science and Engineering2602-42172025-06-0191627710.38088/jise.1375510Comparison of Levenberg-Marquardt and Bayesian Regularization Learning Algorithms for Daily Runoff ForecastingAslı BOR0https://orcid.org/0000-0002-1679-5130Merve OKAN1https://orcid.org/0000-0001-6095-2992Norwegian University of Science and TechnologyIZMIR UNIVERSITY OF ECONOMICSIn 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. http://jise.btu.edu.tr/en/download/article-file/3472764discharge forecastingrainfall-runoff processartificial neural networkeuphrates-tigris basin thanks |
| spellingShingle | Aslı BOR Merve OKAN Comparison of Levenberg-Marquardt and Bayesian Regularization Learning Algorithms for Daily Runoff Forecasting Journal of Innovative Science and Engineering discharge forecasting rainfall-runoff process artificial neural network euphrates-tigris basin thanks |
| title | Comparison of Levenberg-Marquardt and Bayesian Regularization Learning Algorithms for Daily Runoff Forecasting |
| title_full | Comparison of Levenberg-Marquardt and Bayesian Regularization Learning Algorithms for Daily Runoff Forecasting |
| title_fullStr | Comparison of Levenberg-Marquardt and Bayesian Regularization Learning Algorithms for Daily Runoff Forecasting |
| title_full_unstemmed | Comparison of Levenberg-Marquardt and Bayesian Regularization Learning Algorithms for Daily Runoff Forecasting |
| title_short | Comparison of Levenberg-Marquardt and Bayesian Regularization Learning Algorithms for Daily Runoff Forecasting |
| title_sort | comparison of levenberg marquardt and bayesian regularization learning algorithms for daily runoff forecasting |
| topic | discharge forecasting rainfall-runoff process artificial neural network euphrates-tigris basin thanks |
| url | http://jise.btu.edu.tr/en/download/article-file/3472764 |
| work_keys_str_mv | AT aslıbor comparisonoflevenbergmarquardtandbayesianregularizationlearningalgorithmsfordailyrunoffforecasting AT merveokan comparisonoflevenbergmarquardtandbayesianregularizationlearningalgorithmsfordailyrunoffforecasting |