Prediction of compressive strength of nano silica and micro silica from rice husk ash using multivariate regression models
- 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
-
Prediction of compressive strength of nano silica and micro silica from rice husk ash using multivariate regression models ; volume:3 ; number:1 ; day:11 ; month:12 ; year:2024 ; pages:1-13 ; date:12.2024
AI in civil engineering ; 3, Heft 1 (11.12.2024), 1-13, 12.2024
- Urheber
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Raji, Mustapha A.
Falola, Boluwatife M.
Enikuomehin, Jesse T.
Oyelade, Akintoye O.
Abiodun, Yetunde O.
Olaniyi, Yusuf A.
Olagunju, Olusola G.
Anyaegbuna, Kosisochukwu L.
Abdulkareem, Musa O.
Fapohunda, Christopher A.
- Beteiligte Personen und Organisationen
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SpringerLink (Online service)
- DOI
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10.1007/s43503-024-00043-5
- URN
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urn:nbn:de:101:1-2502230605267.948090475896
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:31 MESZ
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Beteiligte
- Raji, Mustapha A.
- Falola, Boluwatife M.
- Enikuomehin, Jesse T.
- Oyelade, Akintoye O.
- Abiodun, Yetunde O.
- Olaniyi, Yusuf A.
- Olagunju, Olusola G.
- Anyaegbuna, Kosisochukwu L.
- Abdulkareem, Musa O.
- Fapohunda, Christopher A.
- SpringerLink (Online service)
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