摘要
煤自燃系统是一个复杂的巨系统,具有规律性、非线性和随机波动性特点,因此在煤自燃预警系统中利用单一的灰色预测方法很难对其动态发展趋势做出准确的预测。针对上述问题,提出一种将灰色模型和马尔科夫模型相结合对煤自燃进行预测的方法。首先建立煤自燃的GM(1,1)模型,其次以GM(1,1)模型预测值为基础进行马尔科夫预测,然后用平均残差修正预测值。仿真结果表明,灰色马尔科夫模型比灰色模型预测精度明显提高,平均误差减少2.24%,为煤层优化检测提供了依据。
Coal spontaneous combustion system is a complex huge system, which owes the characteristics of regular, non-linear and random fluctuations, so it is very difficult for the single Grey prediction method to make accurate predictions of the dynamic development. This paper proposed a method to predict coal spontaneous combustion, which combines Grey GM （ 1,1 ） model with Markov Model. First, the GM （ 1,1 ） model of coal spontaneous combustion was established. Second, the Markov model was used to predict the GM （ 1,1 ） model prediction values. Finally, the prediction values were corrected with the average residual errors. The results show that the GreyMarkov model is more accurate than the single grey prediction model, and the average relative error is reduced by 2.24% than the Grey model.
出处
《计算机仿真》
CSCD
北大核心
2014年第11期416-420,共5页
Computer Simulation
基金
自然科学基金煤炭联合基金项目(51174263)
河南省重点科技公关项目(112102210004)
河南省教育厅自然科学研究计划项目(2010A520020)
