王晶晶,尹晖

• 1:武汉大学测绘学院
• 2:潍坊科技学院建筑工程学院

摘要(Abstract)：

针对高层建筑的沉降监测与趋势预报问题,结合时间序列分析方法,该文提出一种基于ARMA的趋势项和随机项叠加预测法,把沉降监测时间序列数据分解为趋势项与随机项,分别建立趋势回归函数模型与随机项ARMA模型,叠加进行沉降量的预报,并通过上海外滩某高层建筑的沉降监测实例,研究并比较了该方法与传统的ARIMA差分预测法对建筑沉降预报精度的影响。实验结果表明:基于ARMA的趋势项和随机项叠加预测法在沉降预报中精度优于基于ARIMA的差分预测法。该方法利用趋势回归函数的保持作用,克服了传统的时间序列ARIMA模型在长期预测中精度不高的问题,并且随着预测步长的增加,优势更加明显。

关键词(KeyWords)： 沉降监测;ARMA;ARIMA;沉降预报;精度

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(51468040)

作者(Author): 王晶晶,尹晖

DOI: 10.16251/j.cnki.1009-2307.2019.03.018

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