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  INFORMATION THEORY AND ARTIFICIAL INTELLIGENCE TO MANAGE UNCERTAINTY IN HYDRODYNAMIC AND HYDROLOGICAL MODELS

  ABEBE ANDUALEM JEMBERIE

  The complementary nature of physically-based and data-driven models in their demand for physical insight and historical data, leads to the notion that the predictions of a physically-based model can be improved and the associated uncertainty can be systematically reduced through the conjunctive use of a data-driven model of the residuals. The objective of this thesis is to min...

  $2,540.00

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