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    Sustainable Concrete Mix Designs: Multiobjective Optimization through Machine Learning Approaches

    Source: Journal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 004::page 04026033-1
    Author:
    Hammoud, Ahmad
    ,
    Karaki, Ayman
    ,
    Dujovic, Milos
    ,
    Battalgazy, Bekassyl
    ,
    Arroyave, Raymundo
    ,
    Masad, Eyad
    DOI: 10.1061/JCCEE5.CPENG-6748
    Publisher: American Society of Civil Engineers
    Abstract: AbstractDeveloping 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 ...
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      Sustainable Concrete Mix Designs: Multiobjective Optimization through Machine Learning Approaches

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4314425
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    contributor authorHammoud, Ahmad
    contributor authorKaraki, Ayman
    contributor authorDujovic, Milos
    contributor authorBattalgazy, Bekassyl
    contributor authorArroyave, Raymundo
    contributor authorMasad, Eyad
    date accessioned2026-08-20T21:25:21Z
    date available2026-08-20T21:25:21Z
    date copyright2026/03/19
    date issued2026
    identifier otherJCCEE5.CPENG-6748.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314425
    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 ...
    publisherAmerican Society of Civil Engineers
    titleSustainable Concrete Mix Designs: Multiobjective Optimization through Machine Learning Approaches
    typeJournal Article
    journal volume40
    journal issue4
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/JCCEE5.CPENG-6748
    journal fristpage04026033-1
    journal lastpage04026033-15
    page15
    treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 004
    contenttypeFulltext
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