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Analysis of Two-Wheeler Casualty Traffic Accidents with Improved Apriori Algorithm Based on the XGBoost Model

Accurately identifying the significant factors influencing the severity of two-wheeler casualty accidents and mining association rules between multi-factor combinations and accident outcomes is crucial for implementing targeted prevention strategies. This study integrates machine learning and an imp...

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Principais autores: Yansong HU, Changjun WANG, Jinzi ZHENG, Yonggang ZHANG, Tianya DU
Formato: Artigo
Idioma:Inglês
Publicado em: University of Zagreb, Faculty of Transport and Traffic Sciences 2026-05-01
coleção:Promet (Zagreb)
Assuntos:
traffic safety
two-wheeler casualty traffic accident
association rule algorithm
xgboost
weighted support
Acesso em linha:https://traffic2.fpz.hr/index.php/PROMTT/article/view/1233
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