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...
Saved in:
Published in | Journal of Zhejiang University. A. Science Vol. 8; no. 9; pp. 1482 - 1487 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
School of Municipal and Environmental Engineering, Harbin Institute of Technology, Harbin 150090, China
01.08.2007
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
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 |