The revegetation of south dump in Yuanbaoshan open pit coal mine

Keyword(s):  
2012 ◽  
Vol 599 ◽  
pp. 272-277 ◽  
Author(s):  
Zhi Bin Liu ◽  
Xiao Wei Yang

This paper used RBF artificial neural network to evaluate the underground water contaminated by the leachate of waste dump of open pit coal mine of Xinqiu in Fuxin. Firstly, with the advantages of neural network method in dealing with nonlinear problem, the RBF neural network model was built. Then, the normalized standard matrix was taken as training sample and the MATLAB software was used to train the training sample. Finally, the monitoring data were taken as test samples and were inputted in the RBF neural network model to evaluate the groundwater quality of study area. At the same time, the concept of degree of membership was adopted in the result making it more objective and accurate. The result shows that the ground water of this mining is seriously polluted, class of its pollution is Ⅳ-Ⅴ.The method with strong classification function and reliable evaluation results is simple and effective, and can be widely applied in all kinds of water resources comprehensive evaluation.


Author(s):  
Jiachen Wang ◽  
Wenhui Tan ◽  
Shiwei Feng ◽  
Rudi Zhou

2011 ◽  
Vol 5 ◽  
pp. 1116-1120 ◽  
Author(s):  
CHU Daozhong ◽  
ZHU Qingli ◽  
WANG Jie ◽  
ZHAO Xiaozhi

2018 ◽  
Vol 41 ◽  
pp. 01007
Author(s):  
Yuriy Kutepov ◽  
Aleksandr Mironov ◽  
Maksim Sablin ◽  
Elena Borger

This article considers mining and geological conditions of the site “Blagodatny” of the mine named after A.D. Ruban located underneaththe old open pit coal mine and the hydraulic-mine dump. The potentially dangerous zones in the undermined rock mass have been identified based onthe conditions of formation of water inflow into mine workings. Safe depthof coal seams mining has been calculated depending on the type of water body – the hydraulic-mine dump.


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