1st Edition
Information Theory and Artificial Intelligence to Manage Uncertainty in Hydrodynamic and Hydrological Models
By Abebe Andualem Jemberie
Copyright 2004
198 Pages
by
CRC Press
200 Pages
by
CRC Press
184 Pages
by
CRC Press
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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 minimise the... Read more
Part I: Overview; Chapter 1: Introduction; Chapter 2: Background; Part II: Methodology; Chapter 3: Information Theory-Based Approaches; Chapter 4: Artificial Intelligent Approaches; Chapter 5: Complementary Modelling; Part III: Application; Chapter 6: Flow Forecasting on the Rhine and Meuse Rivers; Chapter 7: Forecasting the Accuracy of Numerical Surge Forecasts Along the Dutch Coast; Part IV: Evaluation; Chapter 8: Conclusions, Discussion and Future Work
Biography
Abebe Andualem Jemberie
