Traffic accident severity prediction based on an enhanced MSCPO-XGBoost hybrid model

Traffic accident severity prediction based on an enhanced MSCPO-XGBoost hybrid model

Abstract Road traffic accidents pose a significant threat to public safety in China. This study proposes a novel severity prediction framework based on a Modified Stochastic Crested Porcupine Optimizer (MSCPO) combined with the XGBoost algorithm. The model was trained on 4287 accident cases from Chi...

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Bibliographic Details
Main Authors: Fei Chen, Xiang Qun Liu, Jian Jun Yang, Xu Kang Liu, Jing Hui Ma, Jia Chen, Hua Yu Xiao
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Accident severity prediction
Road traffic accident
XGBoost
MSCPO
SHAP
Online Access:https://doi.org/10.1038/s41598-025-00797-7
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https://doi.org/10.1038/s41598-025-00797-7

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