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Use of Evolutionary Polynomial Regression (EPR) for Prediction of Total Sediment Load of Malaysian Rivers
Nadiatul Adilah Ahmad Abdul Ghani, Mohamed A. Shahin, Hamid R. Nikraz
Pages - 262 - 277     |    Revised - 15-09-2012     |    Published - 24-10-2012
Volume - 6   Issue - 5    |    Publication Date - October 2012  Table of Contents
Sediment, River, Modelling
This study presents the use of Evolutionary Polynomial Regression (EPR) in predicting the total sediment load of ten selected rivers in Malaysia. EPR is a data-driven hybrid technique, based on evolutionary computing. In order to apply the method, the extensive database of the Department of Irrigation and Drainage (DID), Ministry of Natural Resources & Environment, Malaysia was sought, and unrestricted access was granted. The EPR technique produced greatly improved results compared to other previous sediment load methods. 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 performance of the EPR model demonstrates its predictive capability and generalisation ability to solve highly nonlinear problems of river engineering applications, such as sediment.
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2 Jaiyeola, A. T., & Bwapawa, J. K. (2015).Dynamics of sedimentation and use of genetic algorithms for estimating sediment yields in a river: a critical review. natural resource modeling.
3 Shahnazari, H., Shahin, M. A., & Tutunchian, M. A. (2014). Evolutionary-based approaches for settlement prediction of shallow foundations on cohesionless soils. Geotech Eng, 12(1), 55-64.
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Miss Nadiatul Adilah Ahmad Abdul Ghani
Associate Professor Mohamed A. Shahin
Professor Hamid R. Nikraz