新陈代谢灰色模型在地铁变形监测中的应用

Application of Metabolic Grey Model in Subway Deformation Monitoring

针对地铁开挖造成的地表变形预测问题,本文探讨了灰色模型的基本原理与优势,并以某地铁实测变形数据为依据,采用新陈代谢GM(1,1)模型进行建模预测,以ARMA预测模型、GM(1,1)模型分别进行对比分析。通过精度评定,获取可靠结论。实验结果表明,3种预计模型均可获取一定精度的预测值,新陈代谢GM(1,1)模型的预测值准确可靠,精度高于另外两种模型,为同类变形预计的实际工程项目提供了依据,具有参考价值。

For surface deformation prediction caused by subway excavation,this paper discusses the basic principle and advantages of grey model. Based on a subway deformation data,the Information Renewal GM（ 1,1） model was adopted to predicting and modeling,and it was compared with the ARMA forecasting model and GM（ 1,1） models. Reliable conclusions were obtain through precision evaluation. The experimental results show that the three expected model can obtain accurate predictive value,and the prediction result of metabolic GM（ 1,1） model is accurate and reliable and its precision is higher than that other two model. The conclusion of this paper can be provided as the basis for similar deformation project,thus has the reference value.