Flood Forecasting Using Artificial Neural Networks

Flood Forecasting Using Artificial Neural Networks

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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.... warning of flood occurrence is fundamental to reducing the potentially disastrous effects of floods (Ford, 2001). ... They vary according to their data requirements, the computational resources that are necessary for their implementation, and the problem to be ... Data driven methods have been identified as possessing the potential to fulfil these needs, and therefore provided the primary focus of this work.

Title:Flood Forecasting Using Artificial Neural Networks
Author: P Varoonchotikul
Publisher:CRC Press - 2003-01-01

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