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Predicting dynamic deformation of retaining structure by LSSVR-based time series method

  • Tongji University
  • Zhejiang Agriculture and Forestry University
  • Shenzhen University

科研成果: 期刊稿件文章同行评审

50 引用 (Scopus)

摘要

In this paper, we propose a LSSVR-based time series method (LTSM) to predict dynamic lateral deformation of retaining structure and ground surface settlement in deep foundation pit engineering. After reconstructing phase space, time-varying lateral displacement of each observation point on retaining structure can be predicted using its historic unary time series data. And then, the ground settlement nearby the deep foundation pit can be predicted using all the observed values of lateral deformation which were collected at the same time from different depths on the retaining structure. The experimental results show that LTSM achieved a high accuracy when predicting the lateral deformation and ground settlement.

源语言英语
页(从-至)165-172
页数8
期刊Neurocomputing
137
DOI
出版状态已出版 - 5 8月 2014
已对外发布

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