Short communication: Part contour error prediction based on LSTM neural network.

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Title: Short communication: Part contour error prediction based on LSTM neural network.
Authors: Zhang, Yun1,2, zhangyun@tsinghua.edu.cn, Liang, Guangshun1, Cao, Cong3, Li, Yan2
Source: Mechanical Sciences; 2023, Vol. 14 Issue 1, p15-18, 4p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 164804660
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Short communication: Part contour error prediction based on LSTM neural network.
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  Data: <searchLink fieldCode="AU" term="%22Zhang%2C+Yun%22">Zhang, Yun</searchLink><relatesTo>1,2</relatesTo>, <i>zhangyun@tsinghua.edu.cn</i><br /><searchLink fieldCode="AU" term="%22Liang%2C+Guangshun%22">Liang, Guangshun</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Cao%2C+Cong%22">Cao, Cong</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AU" term="%22Li%2C+Yan%22">Li, Yan</searchLink><relatesTo>2</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Mechanical+Sciences%22">Mechanical Sciences</searchLink>; 2023, Vol. 14 Issue 1, p15-18, 4p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=164804660
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.5194/ms-14-15-2023
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 4
        StartPage: 15
    Titles:
      – TitleFull: Short communication: Part contour error prediction based on LSTM neural network.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Zhang, Yun
      – PersonEntity:
          Name:
            NameFull: Liang, Guangshun
      – PersonEntity:
          Name:
            NameFull: Cao, Cong
      – PersonEntity:
          Name:
            NameFull: Li, Yan
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          Dates:
            – D: 01
              M: 01
              Text: 2023
              Type: published
              Y: 2023
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              Value: 21919151
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              Value: 14
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Mechanical Sciences
              Type: main
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