Information Theory and Artificial Intelligence to Manage Uncertainty in Hydrodynamic and Hydrological Models
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 system.
- First published
- 2017
- Publishers
- Taylor & Francis Group
- Language
- English
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