Tree-based logistic regression approach for work zone casualty risk assessment
This study presents a tree-based logistic regression approach to assessing work zone casualty risk, which is defined as the probability of a vehicle occupant being killed or injured in a work zone crash. First, a decision tree approach is employed to determine the tree structure and interacting fact...
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sg-ntu-dr.10356-1071362019-12-06T22:25:28Z Tree-based logistic regression approach for work zone casualty risk assessment Wang, David Zhi Wei Weng, Jinxian. Meng, Qiang. School of Civil and Environmental Engineering DRNTU::Engineering::Civil engineering This study presents a tree-based logistic regression approach to assessing work zone casualty risk, which is defined as the probability of a vehicle occupant being killed or injured in a work zone crash. First, a decision tree approach is employed to determine the tree structure and interacting factors. Based on the Michigan M-94\I-94\I-94BL\I-94BR highway work zone crash data, an optimal tree comprising four leaf nodes is first determined and the interacting factors are found to be airbag, occupant identity (i.e., driver, passenger), and gender. The data are then split into four groups according to the tree structure. Finally, the logistic regression analysis is separately conducted for each group. The results show that the proposed approach outperforms the pure decision tree model because the former has the capability of examining the marginal effects of risk factors. Compared with the pure logistic regression method, the proposed approach avoids the variable interaction effects so that it significantly improves the prediction accuracy. 2013-11-15T06:18:37Z 2019-12-06T22:25:28Z 2013-11-15T06:18:37Z 2019-12-06T22:25:28Z 2013 2013 Journal Article Weng, J., Meng, Q., & Wang, D. Z. W. (2013). Tree-based logistic regression approach for work zone casualty risk assessment. Risk analysis, 33(3), 493-504. 0272-4332 https://hdl.handle.net/10356/107136 http://hdl.handle.net/10220/17683 http://dx.doi.org/10.1111/j.1539-6924.2012.01879.x en Risk analysis |
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DRNTU::Engineering::Civil engineering Wang, David Zhi Wei Weng, Jinxian. Meng, Qiang. Tree-based logistic regression approach for work zone casualty risk assessment |
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This study presents a tree-based logistic regression approach to assessing work zone casualty risk, which is defined as the probability of a vehicle occupant being killed or injured in a work zone crash. First, a decision tree approach is employed to determine the tree structure and interacting factors. Based on the Michigan M-94\I-94\I-94BL\I-94BR highway work zone crash data, an optimal tree comprising four leaf nodes is first determined and the interacting factors are found to be airbag, occupant identity (i.e., driver, passenger), and gender. The data are then split into four groups according to the tree structure. Finally, the logistic regression analysis is separately conducted for each group. The results show that the proposed approach outperforms the pure decision tree model because the former has the capability of examining the marginal effects of risk factors. Compared with the pure logistic regression method, the proposed approach avoids the variable interaction effects so that it significantly improves the prediction accuracy. |
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School of Civil and Environmental Engineering |
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School of Civil and Environmental Engineering Wang, David Zhi Wei Weng, Jinxian. Meng, Qiang. |
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Article |
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Wang, David Zhi Wei Weng, Jinxian. Meng, Qiang. |
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Wang, David Zhi Wei |
title |
Tree-based logistic regression approach for work zone casualty risk assessment |
title_short |
Tree-based logistic regression approach for work zone casualty risk assessment |
title_full |
Tree-based logistic regression approach for work zone casualty risk assessment |
title_fullStr |
Tree-based logistic regression approach for work zone casualty risk assessment |
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Tree-based logistic regression approach for work zone casualty risk assessment |
title_sort |
tree-based logistic regression approach for work zone casualty risk assessment |
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2013 |
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https://hdl.handle.net/10356/107136 http://hdl.handle.net/10220/17683 http://dx.doi.org/10.1111/j.1539-6924.2012.01879.x |
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