Use of Evolutionary Polynomial Regression (EPR) for Prediction of Total Sediment Load of Malaysian Rivers
This study investigates the use of Evolutionary Polynomial Regression (EPR) for predicting the total sediment load of Malaysian rivers. EPR is a data-driven modelling hybrid technique, based on evolutionary computing, that has been recently used successfully in solving many problems in civil enginee...
| Main Authors: | , , |
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| Format: | Journal Article |
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CSC Journals
2012
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| Online Access: | http://hdl.handle.net/20.500.11937/26369 |
| _version_ | 1848751967165218816 |
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| author | Abdul Ghani, Nadiatul Shahin, Mohamed Nikraz, Hamid |
| author_facet | Abdul Ghani, Nadiatul Shahin, Mohamed Nikraz, Hamid |
| author_sort | Abdul Ghani, Nadiatul |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This study investigates the use of Evolutionary Polynomial Regression (EPR) for predicting the total sediment load of Malaysian rivers. EPR is a data-driven modelling hybrid technique, based on evolutionary computing, that has been recently used successfully in solving many problems in civil engineering. In order to apply the method for modelling the total sediment of Malaysian rivers, an extensive database obtained from the Department of Irrigation and Drainage (DID),Ministry of Natural Resources & Environment, Malaysia was sought, and unrestricted access was granted. A robustness study was performed in order to confirm the generalisation ability of the developed EPR model, and a sensitivity analysis was also conducted to determine the relative importance of model inputs. The results obtained from the EPR model were compared with those obtained from six other available sediment load prediction models. The performance of the EPR model demonstrates its predictive capability and generalisation ability to solve highly nonlinear problems of river engineering applications, such as sediment. Moreover, the EPR model produced reasonably improved results compared to those obtained from the other available sediment load methods. |
| first_indexed | 2025-11-14T08:01:08Z |
| format | Journal Article |
| id | curtin-20.500.11937-26369 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:01:08Z |
| publishDate | 2012 |
| publisher | CSC Journals |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-263692017-01-30T12:53:08Z Use of Evolutionary Polynomial Regression (EPR) for Prediction of Total Sediment Load of Malaysian Rivers Abdul Ghani, Nadiatul Shahin, Mohamed Nikraz, Hamid Malaysia sediment prediction Evolutionary polynomial regression rivers This study investigates the use of Evolutionary Polynomial Regression (EPR) for predicting the total sediment load of Malaysian rivers. EPR is a data-driven modelling hybrid technique, based on evolutionary computing, that has been recently used successfully in solving many problems in civil engineering. In order to apply the method for modelling the total sediment of Malaysian rivers, an extensive database obtained from the Department of Irrigation and Drainage (DID),Ministry of Natural Resources & Environment, Malaysia was sought, and unrestricted access was granted. A robustness study was performed in order to confirm the generalisation ability of the developed EPR model, and a sensitivity analysis was also conducted to determine the relative importance of model inputs. The results obtained from the EPR model were compared with those obtained from six other available sediment load prediction models. The performance of the EPR model demonstrates its predictive capability and generalisation ability to solve highly nonlinear problems of river engineering applications, such as sediment. Moreover, the EPR model produced reasonably improved results compared to those obtained from the other available sediment load methods. 2012 Journal Article http://hdl.handle.net/20.500.11937/26369 CSC Journals fulltext |
| spellingShingle | Malaysia sediment prediction Evolutionary polynomial regression rivers Abdul Ghani, Nadiatul Shahin, Mohamed Nikraz, Hamid Use of Evolutionary Polynomial Regression (EPR) for Prediction of Total Sediment Load of Malaysian Rivers |
| title | Use of Evolutionary Polynomial Regression (EPR) for Prediction of Total Sediment Load of Malaysian Rivers |
| title_full | Use of Evolutionary Polynomial Regression (EPR) for Prediction of Total Sediment Load of Malaysian Rivers |
| title_fullStr | Use of Evolutionary Polynomial Regression (EPR) for Prediction of Total Sediment Load of Malaysian Rivers |
| title_full_unstemmed | Use of Evolutionary Polynomial Regression (EPR) for Prediction of Total Sediment Load of Malaysian Rivers |
| title_short | Use of Evolutionary Polynomial Regression (EPR) for Prediction of Total Sediment Load of Malaysian Rivers |
| title_sort | use of evolutionary polynomial regression (epr) for prediction of total sediment load of malaysian rivers |
| topic | Malaysia sediment prediction Evolutionary polynomial regression rivers |
| url | http://hdl.handle.net/20.500.11937/26369 |