改进的灰色系统理论预测矿井涌水量  

Prediction of mine water inflow with modified grey system theory

作　　者：朱愿福[1] 王长申[2] 李彦周 潘扎荣[1] 张亚平[1] 

机构地区：[1]南京大学地球科学与工程学院,江苏南京210046 [2]中国矿业大学资源与地球科学学院,江苏徐州221008 [3]开滦集团荆各庄煤业公司,河北唐山063022

出　　处：《煤田地质与勘探》2014年第4期44-49,54,共7页Coal Geology & Exploration

基　　金：国家自然科学基金项目(50974115)

摘　　要：基于我国东部许多大水矿区煤炭资源日渐枯竭,衰老矿井涌水量变化巨大的现状,以灰色系统理论为基础,提出了一种新的矿井涌水量预测组合模型——GM(1,1)–Markov–新陈代谢组合模型以及用于预测结果综合评价的指数Z。模型验证结果表明,该组合模型的预测结果优于其他模型,减小了序列数据波动性大、新旧信息更替差异所造成的误差,能够较好地解决时间跨度下采空区残留涌水、意外突水等不确定因素对衰老矿井涌水量预测精度和可靠性的影响。将该组合模型及其他模型应用于开滦集团荆各庄衰老矿井涌水量的预测,结果显示:GM(1,1)–Markov–新陈代谢组合模型的综合评价指数最高,达到0.475;荆各庄矿2011—2015年的矿井涌水量将分别为13.055 m3/min、12.730 m3/min、12.579 m3/min、12.493 m3/min和12.503 m3/min。Based on the present status that the coal resources of many coal mine districts are becoming exhausted and the immense changes of aging mine water inflow in East China, this paper improves a new model（GM（1,1）- Markov-Information Renewal combination model） for forecasting mine water inflow and a comprehensive evaluation index（Z） for verifying the prediction by combination model. Verification results of models show that the combination model is superior to other models, because it reduces the error caused by the volatility of the serial data and the differences when replacing the old and new information, and can solve the impact of some uncertain factors（such as water-inrush accidentally and residual water burst, etc.） which affect prediction accuracy and dependability of aging coal mine water inflow over a long time span. The combination model and other models are used for forecasting mine water inflow of Jinggezhuang Mine of Kailuan Group, the results show that the comprehensive evaluation index of GM（1,1）-Markov-Information Renewal combination model is the highest（Z=0.475）, and the predictive inflow values of mine water inflow in 2011-2015 will be 13.055 m3/min, 12.730 m3/min, 12.579 m3/min, 12.493 m3/min and 12.503 m3/min respectively.

关 键 词：矿井涌水量 灰色系统理论 组合模型 综合评价指数 

分 类 号：P641.4[天文地球—地质矿产勘探]