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  4. Hydraulic-hydrologic model for the Zambezi River using satellite data and artificial intelligence techniques
 
doctoral thesis

Hydraulic-hydrologic model for the Zambezi River using satellite data and artificial intelligence techniques

Gamito de Saldanha Calado Matos, José Pedro  
2014
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Type
doctoral thesis
DOI
10.5075/epfl-thesis-6225
Author(s)
Gamito de Saldanha Calado Matos, José Pedro  
Advisors
Schleiss, Anton  
•
Portela Correia dos Santos Ramos da Silva, Maria Manuela
Jury

Prof. J.-L. Scartezzini (président) ; Prof. A. Schleiss, Prof. M.M. Portela Correia dos Santos Ramos da Silva (directeurs) ; Dr J.-M. Fallot, Dr F. Jordan, Dr B. Schaefli (rapporteurs)

Date Issued

2014

Publisher

EPFL

Publisher place

Lausanne

Public defense year

2014-07-11

Thesis number

6225

Subjects

artificial neural networks

•

calibration

•

discharge forecasting

•

hydrological modeling

•

machine learning

•

optimization

•

Pattern-Oriented Memory

•

rainfall interpolation

•

support-vector machines

•

SWAT

•

TRMM

•

uncertainty

•

Zambezi

Note

Co-supervision with: Instituto Superior Técnico (IST) da Universidade de Lisboa, Departamento de Engenharia Civil, Arquitectura e Georrecursos (DECIVIL), Doutoramento em Engenharia Civil

EPFL units
PL-LCH  
Faculty
ENAC  
School
IIC  
Doctoral School
EDEN  
Available on Infoscience
July 9, 2014
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/104964
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