Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels
A vital topic regarding the optimum and economical design of rigid boundary open channels such as sewers and drainage systems is determining the movement of sediment particles. In this study, the incipient motion of sediment is estimated using three datasets from literature, including a wide range o...
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| Format: | Article |
| Language: | English |
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Versita
2016
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| Online Access: | http://ir.unimas.my/id/eprint/13507/ http://ir.unimas.my/id/eprint/13507/7/Design%20of%20a%20new%20hybrid%20artificial%20neural%20network%20method%20based%20on%20decision%20%28abstract%29.pdf |
| _version_ | 1848837422785232896 |
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| author | Isa Ebtehaj Hossein Bonakdari Amir Hossein Zaji Hin Charles Joo Bong Aminuddin Ab Ghani |
| author_facet | Isa Ebtehaj Hossein Bonakdari Amir Hossein Zaji Hin Charles Joo Bong Aminuddin Ab Ghani |
| author_sort | Isa Ebtehaj |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | A vital topic regarding the optimum and economical design of rigid boundary open channels such as sewers and drainage systems is determining the movement of sediment particles. In this study, the incipient motion of sediment is estimated using three datasets from literature, including a wide range of hydraulic parameters. Because existing equations do not consider the effect of sediment bed thickness on incipient motion estimation, this parameter is applied in this study along with the multilayer perceptron (MLP), a hybrid method based on decision trees (DT) (MLP-DT), to estimate incipient motion. According to a comparison with the observed experimental outcome, the proposed method performs well (MARE = 0.048, RMSE = 0.134, SI = 0.06, BIAS = -0.036). The performance of MLP and MLP-DT is compared with that of existing regression-based equations, and significantly higher performance over existing models is observed. Finally, an explicit expression for practical engineering is also provided |
| first_indexed | 2025-11-15T06:39:25Z |
| format | Article |
| id | unimas-13507 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:39:25Z |
| publishDate | 2016 |
| publisher | Versita |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-135072017-02-17T01:46:22Z http://ir.unimas.my/id/eprint/13507/ Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels Isa Ebtehaj Hossein Bonakdari Amir Hossein Zaji Hin Charles Joo Bong Aminuddin Ab Ghani TA Engineering (General). Civil engineering (General) A vital topic regarding the optimum and economical design of rigid boundary open channels such as sewers and drainage systems is determining the movement of sediment particles. In this study, the incipient motion of sediment is estimated using three datasets from literature, including a wide range of hydraulic parameters. Because existing equations do not consider the effect of sediment bed thickness on incipient motion estimation, this parameter is applied in this study along with the multilayer perceptron (MLP), a hybrid method based on decision trees (DT) (MLP-DT), to estimate incipient motion. According to a comparison with the observed experimental outcome, the proposed method performs well (MARE = 0.048, RMSE = 0.134, SI = 0.06, BIAS = -0.036). The performance of MLP and MLP-DT is compared with that of existing regression-based equations, and significantly higher performance over existing models is observed. Finally, an explicit expression for practical engineering is also provided Versita 2016-09-01 Article PeerReviewed text en http://ir.unimas.my/id/eprint/13507/7/Design%20of%20a%20new%20hybrid%20artificial%20neural%20network%20method%20based%20on%20decision%20%28abstract%29.pdf Isa Ebtehaj and Hossein Bonakdari and Amir Hossein Zaji and Hin Charles Joo Bong and Aminuddin Ab Ghani (2016) Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels. Journal of Hydrology and Hydromechanics, 64 (3). pp. 252-260. ISSN 0042790X https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979207673&partnerID=40&md5=078b6838f9c3f08d1191a7cae2025bf8 DOI: 10.1515/johh-2016-0031 |
| spellingShingle | TA Engineering (General). Civil engineering (General) Isa Ebtehaj Hossein Bonakdari Amir Hossein Zaji Hin Charles Joo Bong Aminuddin Ab Ghani Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels |
| title | Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels |
| title_full | Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels |
| title_fullStr | Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels |
| title_full_unstemmed | Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels |
| title_short | Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels |
| title_sort | design of a new hybrid artificial neural network method based on decision trees for calculating the froude number in rigid rectangular channels |
| topic | TA Engineering (General). Civil engineering (General) |
| url | http://ir.unimas.my/id/eprint/13507/ http://ir.unimas.my/id/eprint/13507/ http://ir.unimas.my/id/eprint/13507/ http://ir.unimas.my/id/eprint/13507/7/Design%20of%20a%20new%20hybrid%20artificial%20neural%20network%20method%20based%20on%20decision%20%28abstract%29.pdf |