Study on GM(1，1) Optimization in the Temperature Forecast of Coal Spontaneous Combustion Experiment and Algorithm
LI Bin1, MENG Qing-hua2, LI Hai-tao2, SONG Yuan-xi1
1. Bulianta Mine, Shenhua Shendong Mine Group, Erdos 017209, China; 2. School of Energy, Xi’an University of Science and Technology, Xi’an 710054, China
Based on the basic law of the spontaneous combustion of coal，coal spontaneous combustion experiments according to coal from coal-fired body temperature gray GM (1，1) model based on GM (1，1) model was optimized GM (1，1)，and coal fire temperature was predicted. MATLAB mathematical software programming simulation and model accuracy test results showed that optimization of GM (1，1) model with more precision，GM (1，1) model in the prediction of coal temperature higher practical value was optimized，and the outcome had a guiding role in the set of equipment failure diagnosis.
李 斌，孟清华，李海涛，宋元喜. 优化GM(1，1)模型在煤自然发火实验中的温度预测及算法研究[J]. 煤炭与化工, 2014, 37(5): 76-78，82.
LI Bin, MENG Qing-hua, LI Hai-tao, SONG Yuan-xi. Study on GM(1，1) Optimization in the Temperature Forecast of Coal Spontaneous Combustion Experiment and Algorithm. CCI, 2014, 37(5): 76-78，82.
