Predicting compressive strength of RCFST columns under different loading scenarios using machine learning optimization
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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1 Online-Ressource.
- Sprache
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Englisch
- Erschienen in
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Predicting compressive strength of RCFST columns under different loading scenarios using machine learning optimization ; volume:13 ; number:1 ; day:3 ; month:10 ; year:2023 ; pages:1-14 ; date:12.2023
Scientific reports ; 13, Heft 1 (3.10.2023), 1-14, 12.2023
- Urheber
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Wu, Feng
Tang, Fei
Lu, Ruichen
Cheng, Ming
- Beteiligte Personen und Organisationen
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SpringerLink (Online service)
- DOI
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10.1038/s41598-023-43463-6
- URN
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urn:nbn:de:101:1-2024020512175370376298
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:32 MESZ
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Beteiligte
- Wu, Feng
- Tang, Fei
- Lu, Ruichen
- Cheng, Ming
- SpringerLink (Online service)
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