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随着我国城市的大力发展,城市地铁的建设逐渐成为各大城市的发展目标,由于地铁处于城市地下中心区域,房屋密集、地形复杂,安全等级高,为了确保安全施工,不容有失,否则将会带来不可预估的损失。为了确保施工安全,施工过程中的变形监测是保障安全的重要步骤,它能实时反映施工面的沉降、位移、变形等变化,为了更好的反映其变化,本文在传统的GM(1,1)预测模型基础上,提出了一种运用“幂函数-指数函数”的复合变换来提高原始数据的平滑度,然后对特定年采用多个不同历史数据运用GM(1,1)模型来预测,利用数据融合算法对多次预测的结果进行优化分析,获得精度较高的预测结果。最后通过一个实例对重庆市轨道交通6号线支线建设中的变形监测数据进行处理分析,得到变形预测结果,为施工提供一定的指导作用。
With the vigorous development of our country’s urban areas, the construction of urban metro has gradually become the target of development in major cities. Since the metro is located in the underground center of the city, the houses are dense, the terrain is complex and the security level is high, in order to ensure safe construction, Will bring unpredictable loss. In order to ensure the construction safety, the deformation monitoring during the construction is an important step to ensure safety. It can reflect the changes of settlement, displacement and deformation of the construction surface in real time. In order to reflect the changes better, Based on the predictive model, a composite transformation using “power function - exponential function ” is proposed to improve the smoothness of the original data, and then the GM (1,1) model is adopted by using different historical data for a particular year Prediction, the use of data fusion algorithm to optimize the results of multiple predictions, to obtain high accuracy of the forecast results. Finally, an example is used to analyze the deformation monitoring data in the construction of Chongqing Metro Line 6 feeder and get the results of deformation prediction, which will provide some guidance for the construction.