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dc.contributor.authorLiyungu, Joshua
dc.contributor.authorYu, Bin
dc.date.accessioned2026-08-20T11:33:39Z
dc.date.available2026-08-20T11:33:39Z
dc.date.copyright2026/02/26
dc.date.issued2026
dc.identifier.otherJMCEE7.MTENG-20714.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312374
dc.description.abstractAbstractThe compressive strength of crumb rubberized concrete (CRC) is vital for its structural performance and sustainability. This study integrates XGBoost machine learning with advanced regression and visualization techniques to optimize CRC strength ...Practical ApplicationThis study provides actionable guidance for engineers, contractors, and construction professionals seeking to design sustainable CRC with predictable strength performance. Using advanced machine learning techniques, including XGBoost ...
dc.publisherAmerican Society of Civil Engineers
dc.titleOptimizing Compressive Strength of Crumb Rubber Concrete for Sustainable Construction Using XGBoost and Conceptual Strength Profiles
dc.typeJournal Article
dc.journal.volume38
dc.journal.issue5
dc.journal.titleJournal of Materials in Civil Engineering
dc.identifier.doi10.1061/JMCEE7.MTENG-20714
dc.journal.fristpage04026089-1
dc.journal.lastpage04026089-37
dc.page37
dc.treeJournal of Materials in Civil Engineering:;2026:;Volume ( 038 ):;issue: 005
dc.contenttypeFulltext


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