基于GM-MC模型的唐家庄矿闭坑水位回升预测

Prediction of closed pit water level rise in Tangjiazhuang mine based on GM-MC model

为实现对闭坑矿井水位回升的超前预防预控,结合唐家庄矿已有的观测孔水位回升数据,在传统灰色GM(1,1)模型的基础上建立了灰色--马尔可夫模型。通过对两种预测结果的模拟精度对比分析,最后选择了精度较高的灰色马尔可夫模型对矿井2018年的井内水位进行预测,预测结果的精度为9995%,并且GM-MC模型对水位回升过程的预测与矿井内水位实际回升过程更为适合。在实际工程中,采用灰色--马尔可夫模型对闭坑矿井内的水位回升过程进行预测是可行的,证明此方法对矿井制定针对性的水量排查具有一定的理论依据。

Based on the data of water level rise of Tangjiazhuang mine,a grey Markov model is established based on the traditional grey GM(1,1)model.Through the comparison and analysis of the simulation accuracy of the two prediction results,the gray Markov model with higher accuracy is selected to predict the water level in the mine in 2018,the accuracy of the prediction result is 99.95%,and the prediction of GM-MC model on the water level rise process is more suitable for the actual rise process of the water level in the mine.In the actual project,it is feasible to use the grey Markov model to predict the water level rising process in the closed pit mine,which proves that this method has a certain theoretical basis for the targeted water amount investigation of mines.