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Original scientific paper

Freeway Incident Frequency Analysis Based on CART Method

Xuecai Xu ; Huazhong University of Science and Technology& University of Hong Kong
Željko Šarić ; University of Zagreb
Ahmad Kouhpanejade ; University of Nevada, Las Vegas


Full text: english PDF 793 Kb

page 191-199

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Abstract

Classification and Regression Tree (CART), one of the most widely applied data mining techniques, is based on the classification and regression model produced by binary tree structure. Based on CART method, this paper establishes the relationship between freeway incident frequency and roadway characteristics, traffic variables and environmental factors. The results of CART method indicate that the impact of influencing factors (weather, weekday/weekend, traffic flow and roadway characteristics) of incident frequency is not consistent for different incident types during different time periods. By comparing with Negative Binomial Regression model, CART method is demonstrated to be a good alternative method for analyzing incident frequency. Then the discussion about the relationship between incident frequency and influencing factors is provided, and the future research orientation is pointed out.

Keywords

data mining; classification and regression tree; incident frequency; binary tree

Hrčak ID:

124166

URI

https://hrcak.srce.hr/124166

Publication date:

26.5.2014.

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