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    Use of Evolutionary Polynomial Regression (EPR) for Prediction of Total Sediment Load of Malaysian Rivers

    189007_71025_71159.pdf (408.2Kb)
    Access Status
    Open access
    Authors
    Abdul Ghani, Nadiatul
    Shahin, Mohamed
    Nikraz, Hamid
    Date
    2012
    Type
    Journal Article
    
    Metadata
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    Citation
    Abdul Ghani, Nadiatul A. and Shahin, Mohamed A. and Nikraz, Hamid R. 2012. Use of Evolutionary Polynomial Regression (EPR) for Prediction of Total Sediment Load of Malaysian Rivers. International Journal of Engineering. 6 (5): pp. 262-277.
    Source Title
    International Journal of Engineering
    ISSN
    1985-2312
    URI
    http://hdl.handle.net/20.500.11937/26369
    Collection
    • Curtin Research Publications
    Abstract

    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.

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