Flood Forecasting Using Artificial Neural Networks

1. Auflage 2003
ISBN: 978-90-5809-631-9
Verlag: A A Balkema Publishers

Buch, Englisch, 112 Seiten, Format (B × H): 174 mm x 234 mm, Gewicht: 227 g

Flood disasters continue to occur in many countries in the world and cause tremendous casualties and property damage. To mitigate the effects of floods, a range of structural and non-structural measures have been employed including dykes, channelling, flood-proofing property, land-use regulation and flood warning schemes. Such schemes can include the use of Artificial Neural Networks (ANN) for modelling the rainfall run-off process as it is a quick and flexible approach which gives very promising results. However, the inability of ANN to extrapolate beyond the limits of the training range is a serious limitation of the method, and this book examines ways of side-stepping or solving this complex issue.

Autoren/Hrsg.

Varoonchotikul, P.

Fachgebiete

• Geowissenschaften Geologie Hydrologie, Hydrogeologie
• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik
• Geowissenschaften Umweltwissenschaften Umweltmanagement, Umweltökonomie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Fuzzy-Systeme
• Geowissenschaften Umweltwissenschaften Umwelttechnik
• Geowissenschaften Geologie Limnologie (Süßwasser)
• Geowissenschaften Geologie GIS, Geoinformatik

Inhaltsverzeichnis

1 Introduction 2 Artificial Neural Networks 3 Preliminary considerations 4 Extrapolation management for Artificial Neural Network models of Rainfall-Runoff relationships 5 Recurrent Neural Networks 6 Choice of Input 7 Conclusions and recommendations 8 Samevatting 9 References 10 Data used for the study

Über Autor(innen)

P Varoonchotikul