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Data-Driven Approach to Analyzing Factors Influencing Construction Accident Severity Using SHAP Analysis

dc.contributor.authorSon, Jaehui
dc.contributor.authorJeong, Jaewook
dc.contributor.authorJeong, Jaemin
dc.contributor.authorKumi, Louis
dc.contributor.authorMun, Hyeongjun
dc.date.accessioned2026-08-20T10:41:27Z
dc.date.available2026-08-20T10:41:27Z
dc.date.copyright2025/12/30
dc.date.issued2026
dc.identifier.otherJCEMD4.COENG-17206.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311128
dc.description.abstractAbstractDespite advances in construction safety research, existing studies face critical limitations, including severe data imbalance in accident severity classification and lack of interpretable machine-learning models for factor contribution analysis. ...
dc.publisherAmerican Society of Civil Engineers
dc.titleData-Driven Approach to Analyzing Factors Influencing Construction Accident Severity Using SHAP Analysis
dc.typeJournal Article
dc.journal.volume152
dc.journal.issue3
dc.journal.titleJournal of Construction Engineering and Management
dc.identifier.doi10.1061/JCEMD4.COENG-17206
dc.journal.fristpage04025282-1
dc.journal.lastpage04025282-16
dc.page16
dc.treeJournal of Construction Engineering and Management:;2026:;Volume ( 152 ):;issue: 003
dc.contenttypeFulltext


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