Data mining on Chinese train accidents to derive associated rules

作者：Chen, Dingjun; Xu, Chang'an; Ni, Shaoquan^*

来源：Proceedings of the Institution of Mechanical Engineers - Part F: Journal of Rail and Rapid Transit , 2017, 231(2): 239-252.

DOI：10.1177/0954409715624724

• Train accidents
• rough set theory
• associated rule
• railway safety
• reduct

The costs of fatalities and injuries from train accidents have a great impact on society. As part of our effort to understand the characteristics of past train accidents, this paper presents an analysis of significant train accidents occurring in China from 1954 to 2014. Rough set theory and associated rules approaches are applied in analyzing the collected data. The results show that although most derived rules are unique, some rules are worth noting. Collision accidents generally lead to more casualties than derailment accidents, and the most frequent cause of accidents is human error. Additionally, most train accidents occur during summer. These findings can provide railway leaders with lessons and rules learned from past accidents, thus facilitating the establishment of a safer railway operation environment in China.

• 出版日期2017-2
• 单位西南交通大学