刘正佳,廖孟光,黄志豪,郑敦勇

• 1:湖南科技大学地理空间信息技术国家地方联合工程实验室
• 2:湖南科技大学资源环境与安全工程学院

摘要(Abstract)：

针对传统差分整合自回归移动平均(ARIMA)模型对确定性趋势序列的长期预测效果不佳,且无法直观刻画数据的波动规律等问题,该文提出一种趋势项优化的混合时序模型方法。结合北京某高层建筑物施工实例,首先通过迭代运算得到最优趋势项混合模型,然后分别以ARIMA模型、线性趋势项混合模型以及趋势项优化混合模型对50期沉降数据进行拟合,对未来5期数据进行预测。预测结果表明,趋势项优化模型长期预测精度较高,能更好地解释数据的波动规律。

关键词(KeyWords)： 建筑物沉降;ARIMA;时间序列;混合模型;预测

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(51604108);; 湖南省自然科学基金项目(2019JJ50189);; 湖南省教育厅基金项目(19C0744,17C0636);; 湖南省重点研发课题项目(2018GK2015);; 团队基金项目(CXTD004)

作者(Author): 刘正佳,廖孟光,黄志豪,郑敦勇

DOI: 10.16251/j.cnki.1009-2307.2021.04.007

参考文献(References)：

• [1] 王天应，徐亚明.超高层建筑动态特性监测方法研究[J].测绘通报，2017(4):89-92,144.(WANG Tianying,XU Yaming.Research on dynamic characteristic monitoring methods for super high-rise building[J].Bulletin of Surveying and Mapping,2017(4),89-92,144.)
• [2] 袁长丰，刘颖，李聪明，等.超高层建筑施工过程沉降特征分析[J].测绘科学，2017,42(7):172-177.(YUAN Changfeng,LIU Ying,LI Congming,et al.Analysis of settlement characteristics of an ultrahigh-rise building in the construction process[J].Science of Surveying and Mapping,2017,42(7):172-177.)
• [3] 丁宁，孙英君，崔健，等.高层建筑物变形监测数据处理与分析[J].测绘科学，2011,36(5):93-94.(DING Ning,SUN Yingjun,CUI Jian,et al.Data analysis of foundation settlement of high-rise buildings[J].Science of Surveying and Mapping,2011,36(5):93-94.)
• [4] 刘念武，龚晓南，俞峰，等.软土地区基坑开挖引起的浅基础建筑沉降分析[J].岩土工程学报，2014,36(S2):325-329.(LIU Nianwu,GONG Xiaonan,YU Feng,et al.Settlement of buildings with shallow foundations induced by excavation in soft soils[J].Chinese Journal of Geotechnical Engineering,2014,36(S2):325-329.)
• [5] 王建生.基于时间序列分析的变形预报[J].测绘科学技术学报，2011,28(2):150-152.(WANG Jiansheng.Deformation prediction based on time series analysis[J].Journal of Geomatics Science and Technology,2011,28(2):150-152.)
• [6] 王燕.时间序列分析：基于R[M].北京：中国人民大学出版社，2015.(WANG Yan.Time series analysis with R[M].Beijing:China Renmin University Press,2015.)
• [7] 王卫，杨志强，杨建华，等.变形观测数据时间序列建模中的几个问题[J].地球科学与环境学报，2008,30(2):214-217.(WANG Wei,YANG Zhiqiang,YANG Jianhua,et al.Several important problems in time series modeling of deformation measurement datum[J].Journal of Earth Sciences and Environment,2008,30(2):214-217.)
• [8] 胡波，谭涵.基于ARIMA模型的边坡变形分析与预测[J].测绘通报，2019(6):112-116.(HU Bo,TAN Han.Slope deformation analysis and forecast based on ARIMA model[J].Bulletin of Surveying and Mapping,2019(6):112-116.)
• [9] 刘娜，栾元重，黄晓阳，等.基于时间序列分析的桥梁变形监测预报研究[J].测绘科学，2011,36(6):46-48.(LIU Na,LUAN Yuanzhong,HUANG Xiaoyang,et al.Bridge deformation monitoring and forecasting based on time series analysis[J].Science of Surveying and Mapping,2011,36(6):46-48.)
• [10] 臧妻斌，黄腾.时间序列分析在地铁变形监测中的应用[J].测绘科学，2014,39(7):155-157.(ZANG Qibin,HUANG Teng.Application of time series analysis in subway deformation monitoring[J].Science of Surveying and Mapping,2014,39(7):155-157.)
• [11] 武东辉，田林亚，张金华.小波时间序列在地铁沉降监测中的应用[J].测绘科学，2013,38(2):150-151,149.(WU Donghui,TIAN Linya,ZHANG Jinhua.Application of wavelet time-series in settlement monitoring for urban subway[J].Science of Surveying and Mapping,2013,38(2):150-151,149.)
• [12] 曹净，丁文云，赵党书，等.基于LSSVM-ARMA模型的基坑变形时间序列预测[J].岩土力学，2014,35(S2):579-586.(CAO Jing,DING Wenyun,ZHAO Dangshu,et al.Time series forecast of foundation pit deformation based on LSSVM-ARMA model[J].Rock and Soil Mechanics,2014,35(S2):579-586.)
• [13] 冯绍权，花向红，陶武勇，等.一种基于GA-BP-MC神经网络的高铁桥墩沉降预测模型[J].测绘通报，2019(7):50-53.(FENG Shaoquan,HUA Xianghong,TAO Wuyong,et al.A settlement prediction model of high-speed railway pier based on GA-BP-MC neural network[J].Bulletin of Surveying and Mapping,2019(7):50-53.)
• [14] 王璐，桂占飞.GM-ARMA-BP组合模型在建筑物沉降预测中的应用[J].北京测绘，2019,33(9):1038-1042.(WANG Lu,GUI Zhanfei.Application of GM-ARMA-BP model in the prediction of construction settlement[J].Beijing Surveying and Mapping,2019,33(9):1038-1042.)
• [15] 王晶晶，尹晖.一种建筑沉降叠加预测方法[J].测绘科学，2019,44(3):107-113.(WANG Jingjing,YIN Hui.A method of building settlement superposition prediction based on ARMA model[J].Science of Surveying and Mapping,2019,44(3):107-113.)
• [16] 范晓南，何应鹏.非线性回归的高层建筑沉降变形分析[J].山西建筑，2019,45(5):48-49.(FAN Xiaonan,HE Yingpeng.Settlement analysis of high-rise buildings based on nonlinear regression[J].Shanxi Architecture,2019,45(5):48-49.)