Modeling of River Sediment Estimation Using Artificial Neural Network Method (Case Study: Vanai River)
The purpose of this study was to estimate the amount of sediment of Vanai River in Borujerd. In this research, the characteristics of the sub-basins of this river have been extracted first. These specifications include the physical characteristics of the sub-basins, including the area, the environme...
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Kharazmi University
2022-09-01
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| Series: | تحقیقات کاربردی علوم جغرافیایی |
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| Online Access: | http://jgs.khu.ac.ir/article-1-3169-en.pdf |
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| author | Dariush Abolfathi Aghil Madadi Sayyad Asghari |
| author_facet | Dariush Abolfathi Aghil Madadi Sayyad Asghari |
| author_sort | Dariush Abolfathi |
| collection | DOAJ |
| description | The purpose of this study was to estimate the amount of sediment of Vanai River in Borujerd. In this research, the characteristics of the sub-basins of this river have been extracted first. These specifications include the physical characteristics of the sub-basins, including the area, the environment and length of the waterways, and the characteristics of the river flow, and its sediment content. In the following, multivariate linear regression, multilevel prefabricated neural network (MLP) and radial function-based neural network (RBF) models are used to model sediment estimation. After estimating the model, the mean square error index (RMSE) was used to compare the models and select the best model. Evidence has shown that initially the MLP's neural network model had the best estimate with the lowest error rate (90.44) and then the RBF model (151.44) among the three models. The linear regression model has the highest error rate because only linear relationships between variables are considered. |
| format | Article |
| id | doaj-art-5d6d21a2b2e74651b86c1da45df4d2c3 |
| institution | Kabale University |
| issn | 2228-7736 2588-5138 |
| language | fas |
| publishDate | 2022-09-01 |
| publisher | Kharazmi University |
| record_format | Article |
| series | تحقیقات کاربردی علوم جغرافیایی |
| spelling | doaj-art-5d6d21a2b2e74651b86c1da45df4d2c32025-01-31T17:29:28ZfasKharazmi Universityتحقیقات کاربردی علوم جغرافیایی2228-77362588-51382022-09-0122664156Modeling of River Sediment Estimation Using Artificial Neural Network Method (Case Study: Vanai River)Dariush Abolfathi0Aghil Madadi1Sayyad Asghari2 university of Mohaghagh Ardebili university of Mohaghagh Ardebili university of Mohaghagh Ardebili The purpose of this study was to estimate the amount of sediment of Vanai River in Borujerd. In this research, the characteristics of the sub-basins of this river have been extracted first. These specifications include the physical characteristics of the sub-basins, including the area, the environment and length of the waterways, and the characteristics of the river flow, and its sediment content. In the following, multivariate linear regression, multilevel prefabricated neural network (MLP) and radial function-based neural network (RBF) models are used to model sediment estimation. After estimating the model, the mean square error index (RMSE) was used to compare the models and select the best model. Evidence has shown that initially the MLP's neural network model had the best estimate with the lowest error rate (90.44) and then the RBF model (151.44) among the three models. The linear regression model has the highest error rate because only linear relationships between variables are considered.http://jgs.khu.ac.ir/article-1-3169-en.pdfvanaiوneural networksediment estimationlinear regressionmlprbf |
| spellingShingle | Dariush Abolfathi Aghil Madadi Sayyad Asghari Modeling of River Sediment Estimation Using Artificial Neural Network Method (Case Study: Vanai River) تحقیقات کاربردی علوم جغرافیایی vanaiو neural network sediment estimation linear regression mlp rbf |
| title | Modeling of River Sediment Estimation Using Artificial Neural Network Method (Case Study: Vanai River) |
| title_full | Modeling of River Sediment Estimation Using Artificial Neural Network Method (Case Study: Vanai River) |
| title_fullStr | Modeling of River Sediment Estimation Using Artificial Neural Network Method (Case Study: Vanai River) |
| title_full_unstemmed | Modeling of River Sediment Estimation Using Artificial Neural Network Method (Case Study: Vanai River) |
| title_short | Modeling of River Sediment Estimation Using Artificial Neural Network Method (Case Study: Vanai River) |
| title_sort | modeling of river sediment estimation using artificial neural network method case study vanai river |
| topic | vanaiو neural network sediment estimation linear regression mlp rbf |
| url | http://jgs.khu.ac.ir/article-1-3169-en.pdf |
| work_keys_str_mv | AT dariushabolfathi modelingofriversedimentestimationusingartificialneuralnetworkmethodcasestudyvanairiver AT aghilmadadi modelingofriversedimentestimationusingartificialneuralnetworkmethodcasestudyvanairiver AT sayyadasghari modelingofriversedimentestimationusingartificialneuralnetworkmethodcasestudyvanairiver |