Dynamic graph-enhanced multi-scale attention network for FW-UAV fault diagnosis under small sample.

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Title: Dynamic graph-enhanced multi-scale attention network for FW-UAV fault diagnosis under small sample.
Authors: Yi, Rong1, gs.yyi24@gzu.edu.cn, Lu, Jianguang1, jglu@gzu.edu.cn, Tang, Xianghong1, xhtang@gzu.edu.cn
Source: Applied Soft Computing; Mar2026, Vol. 190, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 191762077
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Dynamic graph-enhanced multi-scale attention network for FW-UAV fault diagnosis under small sample.
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  Data: <searchLink fieldCode="JN" term="%22Applied+Soft+Computing%22">Applied Soft Computing</searchLink>; Mar2026, Vol. 190, pN.PAG-N.PAG, 1p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=191762077
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.asoc.2026.114589
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      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
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      – TitleFull: Dynamic graph-enhanced multi-scale attention network for FW-UAV fault diagnosis under small sample.
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            NameFull: Yi, Rong
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            NameFull: Lu, Jianguang
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            NameFull: Tang, Xianghong
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              Text: Mar2026
              Type: published
              Y: 2026
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              Value: 190
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            – TitleFull: Applied Soft Computing
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