Water quality forecast through application of BP neural network at Yuqiao reservoir

This paper deals with the study of a water quality forecast model through application of BP neural network technique and GUI (Graphical User Interfaces) function of MATLAB at Yuqiao reservoir in Tianjin. To overcome the shortcomings of traditional BP algorithm as being slow to converge and easy to r...

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Bibliographic Details
Published inJournal of Zhejiang University. A. Science Vol. 8; no. 9; pp. 1482 - 1487
Main Authors Zhao, Ying, Nan, Jun, Cui, Fu-yi, Guo, Liang
Format Journal Article
LanguageEnglish
Published School of Municipal and Environmental Engineering, Harbin Institute of Technology, Harbin 150090, China 01.08.2007
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Summary:This paper deals with the study of a water quality forecast model through application of BP neural network technique and GUI (Graphical User Interfaces) function of MATLAB at Yuqiao reservoir in Tianjin. To overcome the shortcomings of traditional BP algorithm as being slow to converge and easy to reach extreme minimum value, the model adopts LM (Levenberg-Marquardt) algorithm to achieve a higher speed and a lower error rate. When factors affecting the study object are identified, the reservoir's 2005 measured values are used as sample data to test the model. The number of neurons and the type of transfer functions in the hidden layer of the neural network are changed from time to time to achieve the best forecast results. Through simulation testing the model shows high efficiency in forecasting the water quality of the reservoir.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1673-565X
1862-1775
DOI:10.1631/jzus.2007.A1482