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Review of Predictions of Tensile and Flexural Properties of Fiber-Reinforced Composites Using Machine Learning Models.

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Title: Review of Predictions of Tensile and Flexural Properties of Fiber-Reinforced Composites Using Machine Learning Models.
Authors: Rahman, Md. Mominur1,2, Ismail, Al Emran2,3, Ramli, Muhammad Faiz3, Rashid, Azrin Hani Abdul1,4, Khan, Tabrej4,5, tsebaey@psu.edu.sa, Ahmed, Omar Shabbir1,4, Sebaey, Tamer A.2,4,5
Source: Journal of Composites Science; Apr2026, Vol. 10 Issue 4, p212, 17p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 193454195
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Review of Predictions of Tensile and Flexural Properties of Fiber-Reinforced Composites Using Machine Learning Models.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Composites+Science%22">Journal of Composites Science</searchLink>; Apr2026, Vol. 10 Issue 4, p212, 17p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=193454195
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.3390/jcs10040212
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 17
        StartPage: 212
    Titles:
      – TitleFull: Review of Predictions of Tensile and Flexural Properties of Fiber-Reinforced Composites Using Machine Learning Models.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Rahman, Md. Mominur
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            NameFull: Ismail, Al Emran
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            NameFull: Ramli, Muhammad Faiz
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            NameFull: Rashid, Azrin Hani Abdul
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            NameFull: Khan, Tabrej
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            NameFull: Ahmed, Omar Shabbir
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            NameFull: Sebaey, Tamer A.
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            – D: 01
              M: 04
              Text: Apr2026
              Type: published
              Y: 2026
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            – TitleFull: Journal of Composites Science
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