运用灰色预测模型可以对矿山开采引起的地表下沉和水平移动的观测数据进行处理与分析,进而确定概率积分法参数.根据潞安矿区司马矿地表移动观测站的实测资料,通过建立灰色预测GM(1,1)模型,利用Matlab对观测数据进行插值处理,获得等间隔数据,求取了概率积分法参数,并进行了相关精度分析.在此基础上,将灰色系统预测方法与曲线拟合方法求取参数的结果进行了对比分析,指出了两种方法存在误差的影响因素.结果表明,运用灰色系统理论求取的概率积分法的参数可靠,体现了动态预测的特点.同时,提出可以通过实施定期等间隔的观测和加大对衰退期的观测次数等措施,提高概率积分法参数的精度.%The observation data of surface subsidence and movement caused by mining can be processed and analyzed by a grey prediction model, and the parameters of a probability integral method are obtained. According to the actual observation data of a surface movement observation station in Sima coalmine of Luan mining district, evenly spaced data are obtained, which is achieved by a grey prediction model GM( 1 ,1) as well as the observation data interpolation handled by Matlab. The parameters of the probability integral method are calculated, and then the relative precision is analyzed. On the basis, the results gained by the method of a grey system prediction and cure fitting are compared and analyzed. Meanwhile, the influence factor of error a-bout two methods is pointed out. The results show that the parameters gained by grey system theory are reliable , and that the features of dynamic prediction are embodied. At the same time, measures are proposed to increase parameter accuracy of the probability integral method, such that regular intervals are carried out, and that the observation time is increased for degenerating stage, and so on.
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