矿区非线性沉降的GM(1,1)预计残差改进模型及应用

矿区地表移动变形关系到矿区安全生产和地面建(构)筑物的安全,对矿区地表进行定期监测并预测具有重要现实意义。矿区地表沉降由于持续时间长,观测数据具有长时序且表现为非线性变化的特征,因此存在建模数据区间难以选取、GM(1,1)模型预测精度不高的问题。针对以上问题,本文建立了基于残差加权改正的GM(1,1)改进模型,提出了先阶段后截尾的建模数据区间选取方法、预测流程和模型精度评定标准。经过实例应用验证,GM(1,1)预计残差改进模型预测精度优于GM(1,1)模型,且先阶段后截尾的建模数据区间选取方法能够提高预测精度。

Improved GM(1,1)model based on predicted residual in mining area with non-linear subsidence and its application

In mining areas,the surface movement and deformation are related to the safety of productionand the safety of ground buildings(structures). It is of great practical significance to regularly monitor and predict the surface movement and deformation in mining areas. Due to the long duration of surface subsidence in the mining areas,the observation data has the characteristics of long time series and nonlinear change,so there are some problems such as difficulty in the selection of modeling data interval and low prediction accuracy of GM(1,1). In view of the above problems,this paper establishes an improved GM(1,1)model based on the residual weighted correction,and puts forward the method of interval selection of modeling data, prediction process and evaluation standard of model accuracy. It is verified by an example that the prediction accuracy of GM(1,1)model is better than that of GM(1,1) model,and the method of interval selection of modeling data from stage to tail can improve the prediction accuracy.