基于R/S分析的矿井涌水量灰色预测  

Grey prediction of mine discharge based on the R/S analysis

作　　者：李建林[1,2] 李志强[1] 王心义[1,2] 郑继东[1,2] 昝明军 

机构地区：[1]河南理工大学资源环境学院,河南焦作454000 [2]中原经济区煤层(页岩)气河南省协同创新中心,河南焦作454000

出　　处：《安全与环境学报》2015年第5期6-10,共5页Journal of Safety and Environment

基　　金：国家自然科学基金项目(41272250);河南省高校科技创新团队支持计划项目(15IRTSTHN027)

摘　　要：矿井涌水量序列具有分形和灰色特征,将R/S分析与灰色系统理论相结合,提出了R/S灰色预测模型以预报矿井涌水量。并以龙门矿为例,对其矿井涌水量进行了R/S分析,确定了Hurst指数和平均循环周期;还在一个周期内进行了涌水量灰色预测。结果表明:龙门矿矿井涌水量平均循环周期为10个月;原本无法进行灰色预测的矿井涌水量序列,经R/S分析后不但可以进行灰色预测,而且预测精度达97.54%,明显高于成熟模型—灰色马尔科夫预测模型的精度。该方法拓宽了分形和灰色理论在涌水量研究中的应用范围。The present paper is aimed at offering a grey prediction of the mining discharge based on the R / S analysis so as to make clear the said discharge sequence both at the fractal and gray characteristic features. In order to predict the mining discharge flow,we have brought about a R / S gray prediction model by combining the gray system theory with R / S（ Rescaled Range） analysis. First of all,we have made an analysis of the mineral discharge sequence by using the R / S analysis method,followed by determining the Hurst exponent and the average cycle. And,then,we have managed to conduct the grey prediction of the mine discharge in one cycle. And,at last,the R / S grey prediction has been tested by using the residual test or the association test. Using monthly the mining discharge data of Longmen Coal Mine from January 2006,to December 2010,we have proposed a mining charge prediction model. The results of our prediction through forecast have shown that the Hurst exponent and the average cycle of the discharge sequences of the aforementioned mine account for0. 8114 and 10 months,respectively,signifying that the discharge sequence proves to be strongly consistent with the impact cycle of approximately 10 months. The grey prediction model is fit for the prediction of the mine discharge at the first quarter of 2010,whose accuracy has reached about 97. 54%. When we compare the grey model with the other two methods,it can be found that：（ 1） The mine discharge sequence（ from January 2006 to December 2010） failed to be used for the gray prediction directly,though the R / S gray forecast model enjoys stronger adaptability in predicting the mine discharge.（ 2） Nevertheless,when the grayMarkov prediction model was used to predict the discharge of Longmen Mine in the same cycle,it was possible to achieve an accuracy of 95. 57%,though it was lower than that obtained by the R / S gray prediction model. Thus,it can be concluded that the R / S gray prediction model can not only extend the application range of frac

关 键 词：安全工程 矿山安全 矿井涌水量 R/S分析 平均循环周期 灰色预测 

分 类 号：X936[环境科学与工程—安全科学]