Information Theory and Artificial Intelligence to Manage Uncertainty in Hydrodynamic and Hydrological Models
ISBN: 9780429179402
Platform/Publisher: Taylor & Francis / CRC Press
Digital rights: Users: Unlimited; Printing: Unlimited; Download: Unlimited
Subjects: Computer Science; Earth Sciences; Artificial Intelligence; Earth Sciences; Hydrology;

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


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