MATEC Web Conf.
Volume 272, 20192018 2nd International Conference on Functional Materials and Chemical Engineering (ICFMCE 2018)
|Number of page(s)||8|
|Published online||13 March 2019|
Traffic accident analysis based on C4.5 algorithm in WEKA
School of Transportation, Southeast University, Nanjing 211189, Jiangsu, China
* Corresponding author: firstname.lastname@example.org
At present, China is in a period of steady development of highways. At the same time, traffic safety issues are becoming increasingly serious. Data mining technology is an effective method for analysing traffic accidents. In-depth information mining of traffic accident data is conducive to accident prevention and traffic safety management. Based on the data of Wenli highway traffic accidents from 2006 to 2013, this study selected factors including time factor, linear factor and driver characteristics as research indicators, and established the decision tree using C4.5 algorithm in WEKA to explore the impact of various factors on the accident. According to the degree of contribution of each variable to the classification effect of the model, various modes affecting the type of the accident are obtained and the overall prediction accuracy is about 80%.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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