使用N-K模型和复杂网络理论研究铁路安全风险的合关系
Jiaxu Chen1,2, Lin Zhao1,2, Jinghui Liu1,2
1China Academy of Railway Sciences, Railway Science & Technology Research & Development Center, Beijing, China.
PloS one
|September 22, 2025
概括
本研究使用复杂的网络N-K模型来分析铁路安全风险. 它发现,人员和设备的合因素,如维护不良和不安全的行为,显著增加了事故风险.
科学领域:
- 铁路安全铁路安全
- 风险分析 风险分析
- 复杂网络理论 复杂网络理论
背景情况:
- 铁路事故带来了重大风险.
- 了解风险因素相互作用对于预防至关重要.
- 现有的模型可能无法完全捕捉复杂的相互依存关系.
研究的目的:
- 量化分析铁路安全风险因素之间的合关系.
- 确定导致铁路事故的关键因素.
- 制定科学策略,防止事故发生.
主要方法:
- 利用一个复杂的基于网络的N-K模型.
- 从事故案例数据中确定了18个铁路安全风险因素.
- 计算发生概率和合值.
- 在风险网络上进行可访问性和中心性分析.
主要成果:
- 事故发生与风险合值成正比.
- 更多的合因素与更高的风险相关.
- 人员和设备因素的结合是主要的事故驱动因素.
- 不充分的维护和不安全的人类行为被确定为关键因素.
结论:
- 有效地管理人员-设备因子合可以减少事故.
- 建议优先考虑对维护不足和人类不安全行为的预防工作.
- N-K模型为分析铁路安全风险提供了一个强大的框架.
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