Understanding Water Level Residuals in Malacca Strait Using Genetic Programming

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@Article{Tay:2016:PE,

• author = "Serene Hui Xin Tay and Vladan Babovic",
• title = "Understanding Water Level Residuals in Malacca Strait Using Genetic Programming",
• journal = "Procedia Engineering",
• volume = "154",
• pages = "1267--1274",
• year = "2016",
• note = "12th International Conference on Hydroinformatics (HIC 2016) - Smart Water for the Future",
• ISSN = "1877-7058",
• DOI = "doi:10.1016/j.proeng.2016.07.458",
• URL = "http://www.sciencedirect.com/science/article/pii/S1877705816318471",
• abstract = "Hydrodynamics are highly complex in Malacca Strait as it is where tides from Indian Ocean and South China Sea interact. Highly varying topography and geometry, river discharges from land and seasonal monsoon climate contribute further complication to the local flow dynamics and usually requires numerical model to resolve. However, no matter how well the numerical model is calibrated, residual will exist due to imperfect description of underlying physics and lack of high quality input data. Numerous studies have applied data-driven methods to correct numerical model prediction by forecasting the residuals, and shown that these methods are undeniably effective and efficient and being great value to more traditional modelling approaches. However, in complex hydrodynamic system of Malacca Strait, instead of simply treating numerical model residual as a numerical mismatch and addressing it as a time series problem by local correction, in this paper a more interesting and meaningful effort to uncover the underlying dynamics is attempted. This paper explores the ability of genetic programming to unearth the embedded components or dependencies of the numerical model residual in Malacca Strait.",
• keywords = "genetic algorithms, genetic programming, water level, residuals, Malacca Strait",

}

Genetic Programming entries for Serene Hui Xin Tay Vladan Babovic

Citations