摘要
提出加权分位数自回归AR(p)模型对路基边坡变形预测的新方法,给出其原理和具体算法。以重庆奉云高速公路某滑坡段为例验证了该方法的有效性,并与其他模型作对比分析。结果表明:新方法的预测效果优于最小二乘参数估计的AR(p)模型、非加权分位数估值的AR(p)模型、ARIMA及EMD-ARIMA模型。
In this paper, a new method of weighted quantile autoregressive AR(p)model for the deformation prediction of subgrade slope is proposed, and its principle and algorithm are put forward. The effectiveness of the method is verified by an example of a landslide section of Fengyun Expressway in Chongqing, and the results are compared with other models. The results show that the new method is better than the AR(p)model of least square parameter estimation, AR(p)model of unweightedquantile estimation, ARIMA model and EMD-ARIMA model.
作者
刘硕
王江荣
LIU Shuo;WANG Jiangrong(College of Information Processing and Control Engineering,Lanzhou Petrochemical University of Vocational Technology,Lanzhou 730060,China)
出处
《国防交通工程与技术》
2023年第1期16-19,40,共5页
Traffic Engineering and Technology for National Defence
基金
兰州市科学技术局计划项目(兰财建发[2019]62号)
兰州市西固区科学技术局计划项目(西科发[2017]29号)
兰州石化职业技术学院教科研项目(KJ2020-2)。
