Forecasting of Suspended Sediment in River Using Artificial Intelligence Methods
Accurate estimation of the amount of suspended sediment in the river is important for protecting and managing water structures. By accurately estimating the amount of suspended matter in streams, important information is obtained by determining the life of water structures, water pollution, and rive...
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| Format: | Article |
| Language: | English |
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Cluj University Press
2025-03-01
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| Series: | Aerul şi Apa: Componente ale Mediului |
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| Online Access: | https://aerapa.conference.ubbcluj.ro/2025/pdf/101_107_Unes_etal_AWC_2025.pdf |
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| author | Fatih ÜNEŞ Bestami TASAR Hakan VARÇIN |
| author_facet | Fatih ÜNEŞ Bestami TASAR Hakan VARÇIN |
| author_sort | Fatih ÜNEŞ |
| collection | DOAJ |
| description | Accurate estimation of the amount of suspended sediment in the river is important for protecting and managing water structures. By accurately estimating the amount of suspended matter in streams, important information is obtained by determining the life of water structures, water pollution, and river transportation. In this study, the West Branch Neversink River near Claryville, USA, was chosen as the study area. 567 real-daily data measured between 2021-2023 were used as the study data. As input parameters of the model; air temperature, precipitation, stream flow and turbidity were selected and sediment amount was estimated. Multi Linear Regression (MLR), M5 Decision Tree (M5 Tree) and Artificial Neural Network (ANN) models were used in sediment estimation. Model results were evaluated according to statistical criteria. As a result, ANN model showed best performance. |
| format | Article |
| id | doaj-art-467a45648f4c41e3946d12853c04af81 |
| institution | Kabale University |
| issn | 2344-4401 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Cluj University Press |
| record_format | Article |
| series | Aerul şi Apa: Componente ale Mediului |
| spelling | doaj-art-467a45648f4c41e3946d12853c04af812025-08-20T03:53:21ZengCluj University PressAerul şi Apa: Componente ale Mediului2344-44012025-03-01202593103https://doi.org/10.24193/AWC2025_09Forecasting of Suspended Sediment in River Using Artificial Intelligence MethodsFatih ÜNEŞ0Bestami TASAR1Hakan VARÇIN2Civil Engineering Department, Iskenderun Technical University, Iskenderun, TURKEYCivil Engineering Department, Iskenderun Technical University, Iskenderun, TURKEYCivil Engineering Department, Iskenderun Technical University, Iskenderun, TURKEYAccurate estimation of the amount of suspended sediment in the river is important for protecting and managing water structures. By accurately estimating the amount of suspended matter in streams, important information is obtained by determining the life of water structures, water pollution, and river transportation. In this study, the West Branch Neversink River near Claryville, USA, was chosen as the study area. 567 real-daily data measured between 2021-2023 were used as the study data. As input parameters of the model; air temperature, precipitation, stream flow and turbidity were selected and sediment amount was estimated. Multi Linear Regression (MLR), M5 Decision Tree (M5 Tree) and Artificial Neural Network (ANN) models were used in sediment estimation. Model results were evaluated according to statistical criteria. As a result, ANN model showed best performance. https://aerapa.conference.ubbcluj.ro/2025/pdf/101_107_Unes_etal_AWC_2025.pdfpredictionm5 decision treesuspended sediment modelingfuzzyregressionartificial neural networks |
| spellingShingle | Fatih ÜNEŞ Bestami TASAR Hakan VARÇIN Forecasting of Suspended Sediment in River Using Artificial Intelligence Methods Aerul şi Apa: Componente ale Mediului prediction m5 decision tree suspended sediment modeling fuzzy regression artificial neural networks |
| title | Forecasting of Suspended Sediment in River Using Artificial Intelligence Methods |
| title_full | Forecasting of Suspended Sediment in River Using Artificial Intelligence Methods |
| title_fullStr | Forecasting of Suspended Sediment in River Using Artificial Intelligence Methods |
| title_full_unstemmed | Forecasting of Suspended Sediment in River Using Artificial Intelligence Methods |
| title_short | Forecasting of Suspended Sediment in River Using Artificial Intelligence Methods |
| title_sort | forecasting of suspended sediment in river using artificial intelligence methods |
| topic | prediction m5 decision tree suspended sediment modeling fuzzy regression artificial neural networks |
| url | https://aerapa.conference.ubbcluj.ro/2025/pdf/101_107_Unes_etal_AWC_2025.pdf |
| work_keys_str_mv | AT fatihunes forecastingofsuspendedsedimentinriverusingartificialintelligencemethods AT bestamitasar forecastingofsuspendedsedimentinriverusingartificialintelligencemethods AT hakanvarcin forecastingofsuspendedsedimentinriverusingartificialintelligencemethods |