Study on rules and its prediction of heavy metal pollution in tailings pond effluent

Author

Rao, Yunzhang ; Zhang, Jianping ; Pan, Jianping ; Chen, Guoliang

Author_Institution

Inst. of Resources & Environ. Eng., Jiangxi Univ. of Sci. & Technol., Ganzhou, China

fYear

2011

fDate

24-26 June 2011

Firstpage

779

Lastpage

782

Abstract

On the basis of the heavy metal pollution datum tested in 162 months uninterruptedly of a tailings pond effluent, this paper studied the rules of heavy metal pollution by applying mathematic statistics method. And the artificial neural network based on the improved BP algorithm is applied to predict the heavy metal ions´ concentration of tailings pond effluent so as to further disclose the pollution characteristics. The results show that: the concentration of heavy metal ions is correlated to time. And such kind of correlation can be expressed with power function and predicted precisely in neural network.

Keywords

backpropagation; effluents; environmental science computing; neural nets; pollution; BP algorithm; artificial neural network; heavy metal ions; heavy metal pollution; mathematic statistics method; pollution characteristics; power function; tailings pond effluent; Artificial neural networks; Effluents; Ions; Metals; Pollution; Testing; Training; heavy metal pollution; neural network forecast; rules; tailings pond effluent;

fLanguage

English

Publisher

ieee

Conference_Titel

Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4244-9172-8

Type

conf

DOI

10.1109/RSETE.2011.5964393

Filename

5964393