Levenberg-Marquardt Algorithm Applied to Forecast the Ice Conditions in Ningmeng Reach of the Yellow River

Author

Yan, Jun ; Cao, Hui ; Wang, Jun ; Liu, Yanfang ; Zhao, Haibin

Author_Institution

North China Univ. of Water Conservancy & Electr. Power, Zhengzhou, China

Volume

1

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

184

Lastpage

188

Abstract

The characters of Ningmeng Reach of the Yellow River are introduced firstly, followed by the fundamental of neural network and its application. Then the main factors which affect the ice conditions in Ningmeng Reach are analyzed. Furthermore, the BP model based on feed-forward back-propagation and improved by the Levenberg-Marquardt algorithm is set up and applied to forecast the ice conditions in Ningmeng Reach. The forecast results in the winter of 2004-2005 are in good agreement with the measured data.

Keywords

backpropagation; feedforward neural nets; forecasting theory; nonlinear programming; water resources; Levenberg-Marquardt algorithm; feedforward backpropagation; ice condition forecast; neural network; Artificial neural networks; Biographies; Geographic Information Systems; Ice; Predictive models; Rivers; Sediments; Technological innovation; Temperature; Water conservation; FFBP model; Ningmeng Reach; artificial neural network; forecast; the Levenberg Marquardt algorithm; the ice conditions;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2009. ICNC '09. Fifth International Conference on

Conference_Location

Tianjin

Print_ISBN

978-0-7695-3736-8

Type

conf

DOI

10.1109/ICNC.2009.396

Filename

5365903