DocumentCode
501407
Title
Water Quality Prediction of Moshui River in China Based on BP Neural Network
Author
Miao, Qun ; Yuan, Hui ; Shao, Changfei ; Liu, Zhiqiang
Author_Institution
Inst. of Environ. & Municipal Eng., Qingdao Technol. Univ., Qingdao, China
Volume
1
fYear
2009
fDate
6-7 June 2009
Firstpage
7
Lastpage
10
Abstract
The north of Jiaozhou Bay has become the important region for the development strategy of Qingdao in China, because the development space of the old city district gets saturated. The Moshui River will become the main contaminated river of this area. Neural network was used to build the water quality prediction model of the discharge outlet of the river to predict the concentration of COD, ammonia nitrogen and mineral oil. According to the result, the harmful effects of the emission can be analyzed and the pollution receiving ability of this area can be identified, which can meet the pollution gross control after the completion of these new and high-tech industry regions.
Keywords
backpropagation; environmental science computing; neural nets; rivers; water quality; BP neural network; China; Moshui River; ammonia nitrogen; high-tech industry regions; mineral oil; pollution gross control; water quality prediction; Cities and towns; Environmentally friendly manufacturing techniques; Industrial pollution; Minerals; Neural networks; Nitrogen; Petroleum; Predictive models; Rivers; Water pollution; BP Neural Network; Moshui River; Water Quality Prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3645-3
Type
conf
DOI
10.1109/CINC.2009.176
Filename
5231722
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