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UAMS: An Unsupervised Anomaly Detection Method Integrating MSAA and SSPCAB.

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Title: UAMS: An Unsupervised Anomaly Detection Method Integrating MSAA and SSPCAB.
Authors: Li, Zhe1 (AUTHOR), Chen, Wenhui1,2 (AUTHOR) whchen@hynu.edu.cn, Wang, Weijie1 (AUTHOR)
Source: Symmetry (20738994). Jul2025, Vol. 17 Issue 7, p1119. 21p.
Database: Academic Search Ultimate
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  Data: UAMS: An Unsupervised Anomaly Detection Method Integrating MSAA and SSPCAB.
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  Data: <searchLink fieldCode="AR" term="%22Li%2C+Zhe%22">Li, Zhe</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Wenhui%22">Chen, Wenhui</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> whchen@hynu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Weijie%22">Wang, Weijie</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Symmetry+%2820738994%29%22">Symmetry (20738994)</searchLink>. Jul2025, Vol. 17 Issue 7, p1119. 21p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=186931400
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        Value: 10.3390/sym17071119
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      – Code: eng
        Text: English
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        PageCount: 21
        StartPage: 1119
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      – TitleFull: UAMS: An Unsupervised Anomaly Detection Method Integrating MSAA and SSPCAB.
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            NameFull: Li, Zhe
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            NameFull: Chen, Wenhui
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              Text: Jul2025
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