Evaluate the compressive strength of fiber-reinforced geopolymer concrete incorporating ground granulated blast furnace slag with machine learning approach.

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Bibliographic Details
Title: Evaluate the compressive strength of fiber-reinforced geopolymer concrete incorporating ground granulated blast furnace slag with machine learning approach.
Authors: Rahman Sobuz MH; Department of Building Engineering and Construction Management, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh., Kabbo MKI; Department of Building Engineering and Construction Management, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh., Mazumder S; Department of Building Engineering and Construction Management, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh., Hoque SMFAB; Department of Building Engineering and Construction Management, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh., Akon MK; Department of Building Engineering and Construction Management, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh., Alameri M; Civil Engineering Department, College of Engineering and Architecture, Umm Al-Qura University, Makkah, 24382, Saudi Arabia., Jameel M; Department of Civil Engineering, College of Engineering, King Khalid University, Abha, Saudi Arabia., Abubakar SA; Department of Civil Engineering, Kampala International University, Western Campus, Ishaka -Bushenyi, Western Region, Kampala, Uganda. saliyu@kiu.ac.ug.
Source: Scientific reports [Sci Rep] 2026 May 08; Vol. 16 (1). Date of Electronic Publication: 2026 May 08.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE; PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2045-2322
DOI:10.1038/s41598-026-51133-6