Lagrange修正的动态GM(1,1)模型在基坑变形预测中的应用

Application of Lagrange Modified Dynamic GM(1,1)Model in Foundation Pit Deformation Prediction

针对原始序列出现较大误差或遗漏时导致预测精度低、残值大的问题,提出了一种基于Lagrange修正的动态GM(1,1)(gray model,GM)模型。该模型首先用Lagrange插值法对原始序列进行修正,其次将修正的数据作为原始数据建立Lagrange修正的GM(1,1)模型,并实时加入最新的监测数据,建立Lagrange修正的动态GM(1,1)模型。以某中心医院基坑监测数据为例进行了计算分析,结果表明,Lagrange修正的动态GM(1,1)模型精度优于传统GM(1,1)模型,能准确地预测基坑变化趋势。

Aiming at the problem of low prediction accuracy and large residual value when a large error or omission occurs in the original sequence,a dynamic GM(1,1)model based on Lagrange correction is proposed.The model first uses Lagrange interpolation to modify the original sequence,then uses the modified data as original data to establish a Lagrange-corrected GM(1,1)model,and adds the latest monitoring data in real-time to create a Lagrange-corrected dynamic GM(1,1)model.Taking the monitoring data of the foundation pit of a hospital as an example,the calculation and analysis are carried out.The results show that the accuracy of the Lagrange-corrected dynamic GM(1,1)model is better than that of the traditional GM(1,1)model and can accurately predict the trend of pit changes.