Articles liés à Information Theory and Artificial Intelligence to Manage...

Information Theory and Artificial Intelligence to Manage Uncertainty in Hydrodynamic and Hydrological Models - Couverture rigide

Jemberie, Abebe Andualem

 
9781138405578: Information Theory and Artificial Intelligence to Manage Uncertainty in Hydrodynamic and Hydrological Models
Couverture rigide
ISBN 10 : 1138405574 ISBN 13 : 9781138405578
Editeur : CRC Press, 2017

Synopsis

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 inevitable mismatch between physically-based models and the actual processes as described by the mismatch between predictions and observations. Principles based on information theory are used to detect the presence and nature of residual information in model errors that might help to develop a data-driven model of the residuals by treating the gap between the process and its (physically-based) model as a separate process. The complementary modelling approach is applied to various hydrodynamic and hydrological models to forecast the expected errors and accuracy, using neural

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l'auteur

Abebe Andualem Jemberie

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
CRC Press
Date d'édition
2017
Langue
anglais
ISBN 10 
1138405574
ISBN 13 
9781138405578
Reliure
Relié
Nombre de pages
202
Coordonnées du fabricant
non disponible
Personne responsable
gpsr@libri.de
gpsr@libri.de

Europaallee 1
Bad Hersfeld
36244
Allemagne