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A multi-view ensemble machine learning approach for 3D modeling using geological and geophysical data.

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Title: A multi-view ensemble machine learning approach for 3D modeling using geological and geophysical data.
Authors: Chu, Deping1, Fu, Jinming2, Wan, Bo2,3, wanbo@cug.edu.cn, Li, Hong1, Li, Lulan1, Fang, Fang2, Li, Shengwen2, Pan, Shengyong4, Zhou, Shunping2
Source: International Journal of Geographical Information Science; Dec2024, Vol. 38 Issue 12, p2599-2626, 28p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 180828465
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: A multi-view ensemble machine learning approach for 3D modeling using geological and geophysical data.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Geographical+Information+Science%22">International Journal of Geographical Information Science</searchLink>; Dec2024, Vol. 38 Issue 12, p2599-2626, 28p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=180828465
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1080/13658816.2024.2394228
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 28
        StartPage: 2599
    Titles:
      – TitleFull: A multi-view ensemble machine learning approach for 3D modeling using geological and geophysical data.
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            NameFull: Chu, Deping
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            NameFull: Fu, Jinming
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            NameFull: Wan, Bo
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            NameFull: Li, Hong
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            NameFull: Li, Lulan
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            NameFull: Fang, Fang
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            NameFull: Li, Shengwen
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            NameFull: Pan, Shengyong
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            – D: 01
              M: 12
              Text: Dec2024
              Type: published
              Y: 2024
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              Value: 38
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              Value: 12
          Titles:
            – TitleFull: International Journal of Geographical Information Science
              Type: main
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