Hybrid deep learning approach for rock tunnel deformation prediction based on spatio-temporal patterns.

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Title: Hybrid deep learning approach for rock tunnel deformation prediction based on spatio-temporal patterns.
Authors: Junfeng Sun1, Yong Fang1 fy980220@swjtu.cn, Hu Luo1, Zhigang Yao1, Long Xiang2, Jianfeng Wang1, Yubo Wang1, Yifan Jiang1
Source: Underground Space (2096-2754). Feb2025, Vol. 20, p100-118. 19p.
Database: Academic Search Ultimate
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Header DbId: asn
DbLabel: Academic Search Ultimate
An: 181994493
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: <searchLink fieldCode="JN" term="%22Underground+Space+%282096-2754%29%22">Underground Space (2096-2754)</searchLink>. Feb2025, Vol. 20, p100-118. 19p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=181994493
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.undsp.2024.04.008
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 19
        StartPage: 100
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      – TitleFull: Hybrid deep learning approach for rock tunnel deformation prediction based on spatio-temporal patterns.
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            NameFull: Junfeng Sun
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            NameFull: Yong Fang
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            NameFull: Hu Luo
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            NameFull: Zhigang Yao
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            NameFull: Long Xiang
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            NameFull: Jianfeng Wang
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            NameFull: Yubo Wang
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            NameFull: Yifan Jiang
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            – D: 01
              M: 02
              Text: Feb2025
              Type: published
              Y: 2025
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              Value: 20
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            – TitleFull: Underground Space (2096-2754)
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