深基坑变形监测数据时序分析法的建模与预报

基坑变形监测的各种数据一般是以时间间隔构成的随机序列,用时间序列分析的方法进行监测数据的建模与预报是有效处理监测数据的一种手段。本文以基坑监测中有代表性的监测数据-锚杆拉力监测为例,用时序分析的方法对监测数据处理、分析、建立适合的模型以及对数据进行预报等过程进行研究和探讨。     

有ARMA噪声的一种参数估计的优效性

对于有ARMA噪声的线性回归模型,本文给出了只用递推进行模型辨识和参数估计的线性方法。若用所计算得到的回归残差作为数据,采用Hannan-Rissanen的线性估计法求ARMA噪声的参数估计,则本文证明了估计是强相容的,且对正态序列,估计具有渐近正态优效性。     

Wave height forecasting by the transfer function model

Three completing methods were introduced in this paper. The data were completed from 1983 to 1988 at the KL and PTC stations. The completed data were called original data. The completing methods were the transfer function with fixed-parameters then built the Transfer Function (TF) model between the two stations. The TF model was used to estimate the wave data of the future. The difference of the estimated data and the original data were conferred in this paper. Two types of forecasting differences were discussed here: (1) the input data year increases from 1 to 6 years, and the difference of the estimated data and the original data were then compared. (2) Use one-year data as the input series to forecast the data of the next five years, and then compare the differences of the estimated data and the original data. After comparing the differences we can know the results. The mean value and the standard deviation of the differences decrease and go more stable as the quantity of the input data year increases. The mean value and the standard deviation of the differences increase and go more unstable as the quantity of the forecasted data year increases. This model can be used to forecast the wave data.     

隧道围岩压力的神经网络时间序列分析

围岩压力是隧道开挖后重要的反馈信息之一,受不确定性因素影响,围岩压力监测数据是一个不平稳的时间序列,包括趋势项和随机项。采用BP网络对不平稳时间序列进行数据拟合,处理趋势部分,利用ARMA模型处理随机部分。结合累进算法,对浙江某新建隧道围岩压力进行时间序列预测。结果表明该方法具有较高的预测精度,最大相对误差为3.73%,能够应用于工程实际当中。     

陕西GPS连续观测网站点时间序列去噪与速度场分析

利用GAMITL/GLOBK软件对陕西GPS连续观测网的站点2008-2014年近6 a的连续观测数据进行处理得到基准站原始时间序列;并采用Kalman、ARMA、BP这3种方法对原始时间序列进行滤波去噪分析,结果表明3种方法都有效地剔除了一定量的噪声,使站点在N,E,U这3个方向上的坐标趋势更加显现,尤其是在选定合适的状态噪声矩阵后Kalman方法要优于其他两种方法。同时去噪得到的陕西连续观测网站点在ITRF2008框架下的速度场精度更高,N方向的平均速度为-0.010 1 m/a,E方向的平均速度为0.033 8 m/a,整体往东南方向位移,渭河盆地和汉中盆地内几个站点沉降量较大。     

新陈代谢灰色模型在地铁变形监测中的应用

针对地铁开挖造成的地表变形预测问题,本文探讨了灰色模型的基本原理与优势,并以某地铁实测变形数据为依据,采用新陈代谢GM(1,1)模型进行建模预测,以ARMA预测模型、GM(1,1)模型分别进行对比分析。通过精度评定,获取可靠结论。实验结果表明,3种预计模型均可获取一定精度的预测值,新陈代谢GM(1,1)模型的预测值准确可靠,精度高于另外两种模型,为同类变形预计的实际工程项目提供了依据,具有参考价值。     

Application of Time-Series Model to Predict Groundwater Dynamic in Sanjiang Plain,Northeast China

To study the groundwater dynamic in the typical region of Sanjiang Plain, long-term groundwater level observation data in the Honghe State Farm were collected and analyzed in this paper. The seasonal and long-term groundwater dynamic was explored. From 1996 to 2008, groundwater level kept declining due to intensive exploitation of groundwater resources for rice irrigation. A decline of nearly 5 m was found for almost all the monitoring wells. A time-series method was established to model the groundwater dynamic. Modeled results by time-series model showed that the groundwater level in this region would keep declining according to the current exploitation intensity. A total dropdown of 1.07 m would occur from 2009 to 2012. Time-series model can be used to model and forecast the groundwater dynamic with high accuracy. Measures including control on groundwater exploitation amount and application of water saving irrigation technique should be taken to prevent the continuing declining of groundwater in the Sanjiang Plain.     

基于时间序列分解的GPS卫星钟差预报

根据二次多项武和灰色模型在卫星钟差预报中的特点,本文提出以ARMA(Autoregressive Moving Aver-age)模型分别进行改进;对IGS(International GPS Service for Geodynamic)提供的精密钟差进行时间序列分解,根据预报时间的长短,趋势项分别采用二次多项式和灰...     

基于残差修正的ARMA模型探测门源MS6.4地震前电离层TEC异常

为提高震前电离层总电子含量(TEC)异常探测的精度,提出利用ARMA模型对预测数据进行残差修正得到TEC参考背景值,并设定相对误差和绝对误差相互制约的限差判决门限。通过对2016-01-21青海门源M_S6.4地震进行研究,验证该方法的有效性。结果表明,震前第5天存在明显的TEC异常现象,震中及附近更大区域内会形成异常范围集中的电离层异常区域,TEC异常峰值点位于震中偏南方向;震中位置与异常区域的中心点并不重合,震中位于负异常区偏东方向、正异常区偏南方向。     

大跨度桥梁风场模拟方法对比研究

本文将基于线性滤波器的ARMA模型应用于大跨度桥梁的风场模拟,推导出自回归(AR)阶数P和滑动回归(MA)阶数q不等情况下,ARMA模型用于模拟多变量稳态随机过程的公式,将ARMA风场模拟方法与目前广泛应用于大跨度桥梁风场模拟的谐波合成法应用于一座实际大跨度斜拉桥的风场模拟,通过对比研究得出一些有意义的结论,并证实了ARMA法能够在保证模拟精度的前提下,大大提高风场模拟的效率。