Test on Flood Prediction-Model Using Artificial Neural Network for ShiiLiAn Hydrologic Station on MinChiang,China

Abstract:

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The establishing of a precise simulation model for runoff prediction in river with several tributaries is the difficulty of flood forecast, which is also one of the difficulties in hydrologic research. Due to the theory of Artificial Neural Network, using Back Propagation algorithm, the flood forecast model for ShiLiAn hydrologic station in Minjiang River is constructed and validated in this study. Through test, the result shows that the forecast accuracy is satisfied for all check standards of flood forecast and then proves the feasibility of using nonlinear method for flood forecast. This study provides a new method and reference for flood control and water resources management in the local region.

Info:

Periodical:

Edited by:

Yuanzhi Wang

Pages:

555-561

DOI:

10.4028/www.scientific.net/AMM.39.555

Citation:

Q. H. Luan et al., "Test on Flood Prediction-Model Using Artificial Neural Network for ShiiLiAn Hydrologic Station on MinChiang,China", Applied Mechanics and Materials, Vol. 39, pp. 555-561, 2011

Online since:

November 2010

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Price:

$35.00

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