Improved Tidal and Non-Tidal Representation of Numerical Models through Data Model Integration

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  author =       "Alamsyah Kurniawan",
  title =        "Improved Tidal and Non-Tidal Representation of
                 Numerical Models through Data Model Integration",
  school =       "National University of Singapore",
  year =         "2013",
  address =      "Singapore",
  keywords =     "genetic algorithms, genetic programming, tidal and
                 non-tidal, Singapore regional waters, hydrodynamic
                 modelling, data model integration, data relationship
                 analysis, data-driven modelling",
  URL =          "",
  URL =          "",
  size =         "202 pages",
  abstract =     "The strategic importance of Singapore regional waters
                 (SRW) has led to numerous studies to understand the
                 physical processes that drive, and are driven, by the
                 hydrodynamics in the SRW. However, due to geo-political
                 realities and its highly complex tidal and non-tidal
                 variation, relatively few studies encompass the region
                 as a whole. The main objective of the research
                 presented in this thesis is to understand, examine and
                 develop effective and efficient methods to improve
                 tidal and non-tidal representation in SRW through data
                 model integration (DMI) approach. In conclusion,
                 several techniques of DMI have been successfully
                 developed and implemented to improve hydrodynamic
                 numerical model performance and to better understand
                 (i) the behaviour of the tide in the region and its
                 sensitivities to changes in tidal boundary forcing and
                 to local depth and friction variation in the narrow
                 regions of the Malacca Strait (ii) the physics of the
                 non-tidal barotropic water levels, currents and their
                 forcing mechanisms for the highly complex Singapore
                 regional waters and (iii) the feasibility of applying
                 mutual information theory and genetic programming as an
                 offline data driven modelling tool to capture the
                 non-tidal barotropic dynamics and then using them for
                 updating the numerical model prediction in real time
  notes =        "Supervisor: Vladan Babovic",

Genetic Programming entries for Alamsyah Kurniawan