Prediction and factor identification for crash severity: comparison of discrete choice and tree-based models

X Wang, SH Kim - Transportation research record, 2019 - journals.sagepub.com
Crash severity is one of the most widely studied topics in traffic safety area. Scholars have
studied crash severity through various types of models. Using the publicly available 2017 …
被引用次数：59 相关文章

Prediction and Factor Identification for Crash Severity: Comparison of Discrete Choice and Tree-Based Models

W Xinyi, KS Hoo - Transportation Research Record, 2019 - scholarworks.bwise.kr
Crash severity is one of the most widely studied topics in traffic safety area. Scholars have
studied crash severity through various types of models. Using the publicly available 2017 …

Prediction and factor identification for crash severity: comparison of discrete choice and tree-based models

X Wang, SH Kim - Transportation research record, 2019 - safetylit.org
Crash severity is one of the most widely studied topics in traffic safety area. Scholars have
studied crash severity through various types of models. Using the publicly available 2017 …

Prediction and Factor Identification for Crash Severity: Comparison of Discrete Choice and Tree-Based Models

X Wang, SH Kim - Transportation Research Record: Journal of the …, 2019 - trid.trb.org
Crash severity is one of the most widely studied topics in traffic safety area. Scholars have
studied crash severity through various types of models. Using the publicly available 2017 …

Prediction and factor identification for crash severity: comparison of discrete choice and tree-based models

X Wang, SH Kim - Transportation research record, 2019 - safetylit.org
Crash severity is one of the most widely studied topics in traffic safety area. Scholars have
studied crash severity through various types of models. Using the publicly available 2017 …