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首页> 外文期刊>Modern Physics Letters, B. Condensed Matter Physics, Statistical Physics, Applied Physics >Exploring significant edges of public transport network under targeted attacks
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Exploring significant edges of public transport network under targeted attacks

机译:在目标攻击下探索公共交通网络的重要边缘

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Edges of public transport network (PTN) play important roles in transporting passengers of cities, especially in metropolises. Understanding the significant edges of PTN can provide insights for managers to increase the efficiency of networks. In this work, we construct a new measure called community bridge (CB), which is based on the number of nodes in communities. We propose an edge removal process to test network efficiency (NE), average transfer times (ATT) and correlation coefficient (CC). For comparison, edge measures of degree product (DP), edge betweenness (EB), edge overlap (EO), closeness centrality index (CCI) are introduced for the process. The results show that there are only 12.6% edges are CBs in the network. Removing edges according to CBs can decrease NE more effectively compared with other indicators. However, it cannot increase the ATTs effectively. It is found that removing edges according to CCI is the most effective way to increase ATT under the outranked 15% edges removed. In addition, the results indicate the CC has very different changes according to the introduced removal strategies.
机译:公共交通网络的边缘(PTN)在运送城市的乘客,特别是在大都市中起着重要作用。了解PTN的重要边缘可以为管理人员提供洞察力,以提高网络的效率。在这项工作中,我们构建了一个名为社区桥(CB)的新措施,基于社区中的节点数量。我们提出了一个边缘去除过程来测试网络效率(NE),平均传输时间(ATT)和相关系数(CC)。为了比较,引入了高度产品(DP),边缘之间(EB),边缘重叠(EO),接近度量指数(CCI)的边缘测量,用于该过程。结果表明,网络中只有12.6%的边缘是CBS。根据CBS去除边缘可以与其他指标相比更有效地减少NE。但是,它无法有效地增加ATT。发现根据CCI去除边缘是增加移除的15%边缘下的att的最有效方法。此外,结果表明,根据介绍的去除策略,CC变化非常不同。

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