Optimization and predictive measurement of compressive strength of iron ore slag modified concrete using data-driven supervised machine learning algorithms.

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Bibliographic Details
Title: Optimization and predictive measurement of compressive strength of iron ore slag modified concrete using data-driven supervised machine learning algorithms.
Authors: Sobuz MHR; Department of Building Engineering and Construction Management, Khulna University of Engineering and Technology, Khulna, 9203, Bangladesh. habib@becm.kuet.ac.bd., Kabbo MKI; Department of Building Engineering and Construction Management, Khulna University of Engineering and Technology, Khulna, 9203, Bangladesh., Alzlfawi A; Department of Civil and Environmental Engineering, College of Engineering, Majmaah University, 11952, Al Majmaah, Saudi Arabia., Alameri M; Civil Engineering Department, College of Engineering and Architecture, Umm Al-Qura University, 24382, Makkah, Saudi Arabia., Lal R; HJ Russell & Company, 171 17Th St NW #1600, Atlanta, GA, 30363, USA., Mansour W; Civil Engineering Department, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh, Egypt., Abubakar SA; Department of Civil Engineering, Kampala International University, Western Campus, Ishaka -Bushenyi, Western Region, Uganda. saliyu@kiu.ac.ug.
Source: Scientific reports [Sci Rep] 2026 Jul 10. Date of Electronic Publication: 2026 Jul 10.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2045-2322
DOI:10.1038/s41598-026-61512-8