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A novel univariate feature selection with ANOVA F-test-based machine learning model for Intrusion Detection Framework of Robotics system.

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Title: A novel univariate feature selection with ANOVA F-test-based machine learning model for Intrusion Detection Framework of Robotics system.
Authors: Verma, Narinder1, Kumar, Neerendra1, Singh, Kuljeet2, Aljohani, Abeer3, Sinha, Anurag4, Hussain, Syed Abid5, dr.abid@bakhtar.edu.af
Source: Applied Artificial Intelligence; Dec2025, Vol. 39 Issue 1, p1-20, 20p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 189934099
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PubType: Academic Journal
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  Data: A novel univariate feature selection with ANOVA F-test-based machine learning model for Intrusion Detection Framework of Robotics system.
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  Data: <searchLink fieldCode="JN" term="%22Applied+Artificial+Intelligence%22">Applied Artificial Intelligence</searchLink>; Dec2025, Vol. 39 Issue 1, p1-20, 20p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=189934099
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      – Type: doi
        Value: 10.1080/08839514.2025.2539395
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      – Code: eng
        Text: English
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        PageCount: 20
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      – TitleFull: A novel univariate feature selection with ANOVA F-test-based machine learning model for Intrusion Detection Framework of Robotics system.
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            NameFull: Verma, Narinder
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            NameFull: Kumar, Neerendra
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            NameFull: Singh, Kuljeet
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            NameFull: Aljohani, Abeer
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            NameFull: Sinha, Anurag
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            – D: 01
              M: 12
              Text: Dec2025
              Type: published
              Y: 2025
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            – TitleFull: Applied Artificial Intelligence
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