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dc.contributor.authorHammoud, Ahmad
dc.contributor.authorKaraki, Ayman
dc.contributor.authorDujovic, Milos
dc.contributor.authorBattalgazy, Bekassyl
dc.contributor.authorArroyave, Raymundo
dc.contributor.authorMasad, Eyad
dc.date.accessioned2026-08-20T21:25:21Z
dc.date.available2026-08-20T21:25:21Z
dc.date.copyright2026/03/19
dc.date.issued2026
dc.identifier.otherJCCEE5.CPENG-6748.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314425
dc.description.abstractAbstractDeveloping concrete mix designs that enhance structural performance while reducing environmental impact is vital for achieving sustainable construction. This study utilizes multiobjective optimization and machine learning (ML) that aim to reduce ...Practical ApplicationsThis study provides a practical framework for engineers and project teams to design concrete that balances strength with a reduced carbon footprint. Using more than one thousand real mix records, machine learning models predict ...
dc.publisherAmerican Society of Civil Engineers
dc.titleSustainable Concrete Mix Designs: Multiobjective Optimization through Machine Learning Approaches
dc.typeJournal Article
dc.journal.volume40
dc.journal.issue4
dc.journal.titleJournal of Computing in Civil Engineering
dc.identifier.doi10.1061/JCCEE5.CPENG-6748
dc.journal.fristpage04026033-1
dc.journal.lastpage04026033-15
dc.page15
dc.treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 004
dc.contenttypeFulltext


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