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

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, Y. Cheng, Z. X. Ima, "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
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