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
Link To Document :
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