基于灰色时序组合模型的基坑监测预测

基坑监测是确保矿山基坑工程安全实施的必要手段，不同模型所监测到的基坑沉降值存在一定的差异，因而如何选择一种有效的组合模型是准确预测未来某一时刻基坑沉降面临的主要问题。本研究将时间序列预测模型与灰色模型相结合（即灰色时序组合预测模型）应用于某深基坑（基坑深5.7~13.7 m）沉降监测数据分析，预测结果准确可靠。同时，与单一模型（如ARIMA和GM（1，1））的预测结果相比，灰色时序组合模型的预测精度更高，所获得的预测结果与实测值最接近，是一种非常有效的基坑预测方法。

Monitoring Predication of Foundation Based on Grey Timing Model

Foundation monitoring was necessary methods to ensure the implementation of foundation engineering safety in mines.Because the different models for the settlement of foundation monitoring exists certain difference,therefore,how to select an effective portfolio model that can predict the settlement of foundation pit accurately at a certain time in the future was the main problems.In this research,the time series prediction model and grey model（gray sequence combination forecast model）were employed to a deep foundation pit（5.7-13.7 m deep foundation pit） subsidence monitoring data analysis,and the predicted results were accurate and reliable.Meanwhile,compared with the predicted results of single model（such as ARIMA and GM（1,1））,prediction accuracy of the gray timing sequence model was much higher.The predicted results that we obtained were the closest to the measured values,which presented it was a extremely effective prediction method for foundation pit.