Forecast of coal spontaneous combustion with artificial neural network model based on testing and monitoring gas indices

Author:

Zhang Xin-hai,Wen Hu,Deng Jun,Zhang Xi-chen,Tien Jerry C.

Publisher

Springer Science and Business Media LLC

Subject

Geotechnical Engineering and Engineering Geology,Energy Engineering and Power Technology

Reference10 articles.

1. He P, Wang F Y, Tang X X, 1994. Character of gaseous products of coal oxidation and selection of index gases of coal spontaneous combustion. Journal of China Coal Society, 19(6): 635–642.

2. He Q L, Dai D L, Wang D M, 2003. Critical value of CO of forecasting coal spontaneous combustion. Journal of China University of Mining and Technology, 13(2): 121–125.

3. Lu P, Liao G X, Sun J H, Li P D, 2004. Experimental research on index gas of the coal spontaneous at low-temperature stage. Journal of Loss Prevention in the Process Industries, 17(3): 243–247.

4. Ren T X, Edwardsa J S, Clarkeb D, 1999. Adiabatic oxidation study on the propensity of pulverised coals to spontaneous combustion. Fuel, 78(14): 1 611–1 620.

5. Tan P F, Zhang C S, 2004. Artificial neural network and modeling evolution calculation. Beijing: Tsinghua University Press.

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