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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams.

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Title: Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams.
Authors: Shafighfard, Torkan1, Kazemi, Farzin2,3, Bagherzadeh, Faramarz4, fabagher@uni-bremen.de, Mieloszyk, Magdalena1, Yoo, Doo‐Yeol5, dyyoo@yonsei.ac.kr
Source: Computer-Aided Civil & Infrastructure Engineering; Dec2024, Vol. 39 Issue 23, p3573-3594, 22p
Database: Applied Science & Technology Source
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PubType: Academic Journal
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  Data: Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams.
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  Data: <searchLink fieldCode="JN" term="%22Computer-Aided+Civil+%26+Infrastructure+Engineering%22">Computer-Aided Civil & Infrastructure Engineering</searchLink>; Dec2024, Vol. 39 Issue 23, p3573-3594, 22p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=180951774
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        Value: 10.1111/mice.13164
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      – Code: eng
        Text: English
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        PageCount: 22
        StartPage: 3573
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      – TitleFull: Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams.
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            NameFull: Shafighfard, Torkan
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            NameFull: Kazemi, Farzin
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              M: 12
              Text: Dec2024
              Type: published
              Y: 2024
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