| 加权复合分位数自回归模型在隧道围岩变形预测中的应用 |
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| 引用本文： | 王江荣.加权复合分位数自回归模型在隧道围岩变形预测中的应用[J].大地测量与地球动力学,2017,37(5):511-515. |
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| 作者姓名： | 王江荣 |
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| 摘 要： | 提出加权复合分位数自回归模型对隧道围岩变形进行预测的新方法，并给出其原理和实现算法。以昆明市阳宗隧道为例，对加权复合分位数自回归预测模型进行计算，并与其他模型进行对比分析。结果表明，新方法预测效果优于非加权复合分位数估值的AR(2)模型、基于最小二乘参数估计的自回归预测、经遗传算法优化的支持向量机等预测方法。
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| 关 键 词： | 隧道围岩变形 AR(2)模型 加权复合分位数自回归 模拟退火算法 模型预测分析 |
Application of Weighted Composite Quantile Autoregressive Model in Processing of Rock Surrounding Tunnel Displacement Data |
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| WANG Jiangrong.Application of Weighted Composite Quantile Autoregressive Model in Processing of Rock Surrounding Tunnel Displacement Data[J].Journal of Geodesy and Geodynamics,2017,37(5):511-515. |
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| Authors: | WANG Jiangrong |
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| Abstract: | In this paper, a method for predicting the deformation of rock surrounding a tunnel is put forward based on the weighted composite quantile autoregressive model, giving the principle and algorithm of the method. Using a case study of Yangzong tunnel in Kunming, the weighted composite quantile autoregressive prediction model is calculated and compared with other models. The results show that the forecast effect is better than that of the AR(2) model of the non-weighted composite quantile estimation, the auto regression prediction based on least square parameter estimation, the support vector machine optimized by genetic algorithm and some other prediction methods. |
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| Keywords: | tunnel surrounding rock deformation AR(2) model weighted composite quantile autoregressive simulated annealing algorithm model prediction analysis |
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