Uncertainty Analysis in Rainfall-Runoff Modelling - Application of Machine Learning Techniques: UNESCO-IHE PhD Thesis - Tapa blanda

Shrestha, Durga Lal

 
9780415565981: Uncertainty Analysis in Rainfall-Runoff Modelling - Application of Machine Learning Techniques: UNESCO-IHE PhD Thesis
Tapa blanda
ISBN 10: 0415565987 ISBN 13: 9780415565981
Editorial: CRC Press, 2009

Sinopsis

This book describes the use of machine learning techniques to build predictive models of uncertainty with application to hydrological models, focusing mainly on the development and testing of two different models. The first focuses on parameter uncertainty analysis by emulating the results of Monte Carlo simulation of hydrological models using efficient machine learning techniques. The second method aims at modelling uncertainty by building an ensemble of specialized machine learning models on the basis of past hydrological model’s performance. The book then demonstrates the capacity of machine learning techniques for building accurate and efficient predictive models of uncertainty.

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Acerca del autor

Durga Lal Shrestha is a researcher in the Hydroinformatics and Knowledge Management Department of the UNESCO-IHE Institute for Water Education, Netherlands. He received his Masters degree in hydroinformatics from the UNESCO-IHE Institute for Water Education in 2002. His research interests include hydrological modelling, uncertainty analysis, global and evolutionary optimisation, machine learning techniques and their applications in water based systems.

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Editorial
CRC Press
Año de publicación
2009
Idioma
Inglés
ISBN 10 
0415565987
ISBN 13 
9780415565981
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
222
Contacto del fabricante
no disponible
Persona responsable
no disponible

Otras ediciones populares con el mismo título

9781138424098: Uncertainty Analysis in Rainfall-Runoff Modelling - Application of Machine Learning Techniques: UNESCO-IHE PhD Thesis

Edición Destacada

ISBN 10:  1138424099 ISBN 13:  9781138424098
Editorial: CRC Press, 2017
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