东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2011, Vol. 32 ›› Issue (8): 1195-1197.DOI: -

• 论著 • 上一篇    下一篇

基于小波去噪的改进灰色自适应变形预测

沙成满;韩合新;杨冬梅;   

  1. 东北大学资源与土木工程院;东北大学理学院;
  • 收稿日期:2013-06-19 修回日期:2013-06-19 发布日期:2013-04-04
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    辽宁省自然科学基金资助项目(20102058)

Deformation forecast using improved self-adaptive grey model based on wavelet denoising

Sha, Cheng-Man (1); Han, He-Xin (2); Yang, Dong-Mei (2)   

  1. (1) School of Resources and Civil Engineering, Northeastern University, Shenyang 110819, China; (2) School of Sciences, Northeastern University, Shenyang 110819, China
  • Received:2013-06-19 Revised:2013-06-19 Published:2013-04-04
  • Contact: Han, H.-X.
  • About author:-
  • Supported by:
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摘要： 针对变形量的预测问题,研究了基于小波去噪的改进灰色自适应预测模型.由于监测变形体时很多因素会使测量数据与实际变形数据有偏差,因此首先利用小波去噪方法对变形监测数据序列进行去噪处理,然后再利用灰色自适应模型预测变形量;并对模型的初值进行了修正.最后对一组基坑变形监测数据实例进行分析,表明该方法比单一灰色预测模型更加有效.

关键词: 小波去噪, 自适应模型, 灰色模型, 变形预测, 基坑

Abstract: An improved self-adaptive grey model based on wavelet denoising is studied to forecast the deformation of foundation trenches. As many factors may cause measured data to deviate from the real data during monitoring the deforming foundation trenches, a wavelet denoising method is first used to deal with the measured data of deformation. Then, the self-adaptive grey model is used to forecast the deformation with the initial value amended. An example based on the measured data of a foundation trench is given to show that deformation forecast results by the method combining the wavelet denoising and grey model is more precise than those by a conventional single grey model.

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