公共交通基础设施联网络的基于的节点重要性识别方法:成都的案例研究
Ziqiang Zeng1, Yupeng Sun1, Xinru Zhang2
1Business School, Sichuan University, Chengdu 610065, China.
Entropy (Basel, Switzerland)
|February 23, 2024
概括
在复杂的公共交通网络中确定关键节点对于城市规划和弹性至关重要. 本研究介绍了一种基于的方法,可以改善节点重要性识别,提高网络效率和稳定性.
科学领域:
- 城市规划和交通网络.
- 网络科学和复杂系统科学.
- 信息理论和度指标的信息理论和度指标
背景情况:
- 公共交通系统是复杂的,连接网络 (例如,公共汽车和地铁线路).
- 有效的规划和弹性需要准确识别关键网络节点.
- 现有的中心性指标可能无法完全捕捉结合城市交通系统中的节点重要性.
研究的目的:
- 为结合的公共交通网络开发基于的节点重要性识别方法.
- 加强城市公共交通和交通流程的综合规划.
- 改进网络信息的传播和保持网络的弹性.
主要方法:
- 开发了一种基于的系统度量,整合了五种中心度量:中心度度 (DC),中间中心度 (BC),接近中心度 (CC),自向量中心度 (EC) 和聚类系数 (CCO).
- 通过考虑结节及其联网络中的邻居的信息来确定重要的节点.
- 在成都使用现实世界公交-地铁联网 (10,652个节点,15,476个边缘) 评估了该方法.
主要成果:
- 与单独的功率定律函数相比,多功能配件分析提高了30%的分析准确性.
- 改进的基于的指标显著提高了识别CC和CCO的重要节点的性能.
- 该方法基于使用MCC,NE,S和NC指标的评估,证明了良好的网络弹性.
结论:
- 提出的基于的方法有效地识别复杂的关键节点,合的公共交通网络.
- 这种方法为城市交通规划和网络管理提供了更准确,更强大的工具.
- 这些发现有助于提高城市公共交通系统的弹性和效率.
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