Crash Severity Analysis of Highways Based on Multinomial Logistic Regression Model, Decision Tree Techniques, and Artificial Neural Network: A Modeling Comparison
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- Miaomiao Yan & Yindong Shen, 2022. "Traffic Accident Severity Prediction Based on Random Forest," Sustainability, MDPI, vol. 14(3), pages 1-13, February.
- Fu Wang & Jing Wang & Xianfeng Zhang & Dengjun Gu & Yang Yang & Hongbin Zhu, 2022. "Analysis of the Causes of Traffic Accidents and Identification of Accident-Prone Points in Long Downhill Tunnel of Mountain Expressways Based on Data Mining," Sustainability, MDPI, vol. 14(14), pages 1-22, July.
- Alicja Wolny-Dominiak & Tomasz Żądło, 2021. "The Measures of Accuracy of Claim Frequency Credibility Predictor," Sustainability, MDPI, vol. 13(21), pages 1-13, October.
- Debela Jima & Tibor Sipos, 2022. "The Impact of Road Geometric Formation on Traffic Crash and Its Severity Level," Sustainability, MDPI, vol. 14(14), pages 1-25, July.
- Mubarak Alrumaidhi & Hesham A. Rakha, 2022. "Factors Affecting Crash Severity among Elderly Drivers: A Multilevel Ordinal Logistic Regression Approach," Sustainability, MDPI, vol. 14(18), pages 1-12, September.
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Keywords
crash severity; multinomial logistic regression model; decision tree techniques; artificial neural network;All these keywords.
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