Study on Back-Propagation Neural Networks in Hydrological Forecast

Ri Jun Zhang; Zhong Sheng Li

doi:10.4028/www.scientific.net/AMM.687-691.2153

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 687-691Study on Back-Propagation Neural Networks in...

Study on Back-Propagation Neural Networks in Hydrological Forecast

Abstract:

The hydrological forecasting model are established respectively by the traditional method and the new methods, BP network and projection pursuit, in order to study the feasibility and practicality. The result shows that the accuracy of the BP model is within 10%, has better forecasting effect and more practical value than the others.

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Periodical:

Applied Mechanics and Materials (Volumes 687-691)

Pages:

2153-2156

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.687-691.2153

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Online since:

November 2014

Authors:

Ri Jun Zhang, Zhong Sheng Li

Keywords:

BP Network, Multiple Linear Regressions, Projection Pursuit, Runoff Forecasting

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