摘要
为了预测边坡变形大小,以便及时采取防治措施,通过取不同的迟滞时间对原始监测数据进行相空间重置获得新的数据序列,再以这些新的数据序列为基础,采用预测残差平方和最小的线性优化方法,将ARMA时间序列法和GM(1,1)灰色理论的预测结果进行组合,对某矿的边坡变形量进行滚动组合预测。对不同方法的预测精度和预测残差的标准差进行了对比分析,结果对比表明,组合预测较单项预测方法残差标准差明显减小,且相空间重置后的组合预测结果提高了直接预测的平均预测精度,这为边坡变形趋势的预测与防灾预警提供了可靠的方法。
For predicting a mine＇s slope deformation so as to adopt timely safety measures,this paper proposes a new dynamic synthetical prediction method. With the help of phase- space reconstruction by substituting different lag time,a new data series from the original monitoring data was get for this method. It took the linear optimization method,which on the condition of the minimum sum of squares of prediction residue error,to calculate the weights of different methods＇ predictions,such as ARMA time series and GM（ 1,1） grey theory. The comparison of the results indicates that,the standard deviation of the synthetical prediction is reduced obviously compared with independent approaches; predictions after the Phase-space reconstruction can improve the average precision. And this provides a reliable method for the forecast and precaution for each kind of landslide.
出处
《工程地质学报》
CSCD
北大核心
2016年第6期1041-1047,共7页
Journal of Engineering Geology
基金
国家自然科学基金(41172250)
国家十二五科技支撑项目(2012BAK09B06)
北京市创新团队提升计划项目(IDHT20140501)
北京市科研基地建设-科研创新平台
科研专项-冲击地压微震监测与预警体系的构建(XN083)
新型锚杆加固技术现场试验研究及研究生能力实训(XN107)资助
关键词
边坡变形
滚动组合预测
相空间重置
迟滞时间
Slope deformation
Dynamic synthetical prediction
Phase-space reconstruction
Delay time
