| 灰色稳健总体最小二乘估计及高铁路基变形预测 |
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| 引用本文： | 陈洋,文鸿雁,覃辉,王清涛,周吕.灰色稳健总体最小二乘估计及高铁路基变形预测[J].大地测量与地球动力学,2018,38(2):140-146. |
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| 作者姓名： | 陈洋 文鸿雁 覃辉 王清涛 周吕 |
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| 作者单位： | 桂林理工大学测绘地理信息学院;武汉大学测绘学院;东华理工大学江西省数字国土重点实验室; |
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| 摘 要： | 最小二乘估计和部分变量误差模型的总体最小二乘估计不具备抵御粗差的能力。鉴于粗差可能同时出现在灰色白化微分方程的观测值和系数矩阵中，本文提出基于IGGⅢ抗差方案的部分变量总体最小二乘稳健估计。结合仿真数据和高铁路基观测数据，系统地比较稳健最小二乘、部分变量总体最小二乘、本文算法参数估计结果和算法稳定性。结果表明，本文算法预测精度高，可以应用到高铁路基沉降预测中。
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| 关 键 词： | 部分变量总体最小二乘稳健估计 GM(1 1) 高铁路基沉降预测 |
Robust Total Least Squares Estimated in GM(1,1) for High-Speed Railway Foundation Deformation Prediction |
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| CHEN Yang,WEN Hongyan,QIN Hui,WANG Qingtao,ZHOU Lü.Robust Total Least Squares Estimated in GM(1,1) for High-Speed Railway Foundation Deformation Prediction[J].Journal of Geodesy and Geodynamics,2018,38(2):140-146. |
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| Authors: | CHEN Yang WEN Hongyan QIN Hui WANG Qingtao ZHOU Lü |
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| Abstract: | Least squares estimation and partial errors-in variables total least squares donot have the ability to resist gross errors. As gross error may also appear in the observed value and the coefficient matrix in differential equations, this paper puts forward a partial errors-invariables total least squares model based on IGGⅢ differential resistance. This paper also compares the robust least squares,partial errors-in variables total least squares with the new algorithm systematically,usingparameter estimation results, stability through simulation data, and high-speed railway observations data. The results show that the new algorithm's accuracy is high, which can be applied to the high-speed railway subsidence prediction. |
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| Keywords: | robust partial errors-in variables total least squares estimation GM(1 1) high-speed railway subsidence prediction |
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