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Complex Network Theory Applied to the Growth of Kuala Lumpur’s Public Urban Rail Transit Network

机译:复杂网络理论在吉隆坡公共城市轨道交通网络发展中的应用

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摘要

Recently, the number of studies involving complex network applications in transportation has increased steadily as scholars from various fields analyze traffic networks. Nonetheless, research on rail network growth is relatively rare. This research examines the evolution of the Public Urban Rail Transit Networks of Kuala Lumpur (PURTNoKL) based on complex network theory and covers both the topological structure of the rail system and future trends in network growth. In addition, network performance when facing different attack strategies is also assessed. Three topological network characteristics are considered: connections, clustering and centrality. In PURTNoKL, we found that the total number of nodes and edges exhibit a linear relationship and that the average degree stays within the interval [2.0488, 2.6774] with heavy-tailed distributions. The evolutionary process shows that the cumulative probability distribution (CPD) of degree and the average shortest path length show good fit with exponential distribution and normal distribution, respectively. Moreover, PURTNoKL exhibits clear cluster characteristics; most of the nodes have a 2-core value, and the CPDs of the centrality’s closeness and betweenness follow a normal distribution function and an exponential distribution, respectively. Finally, we discuss four different types of network growth styles and the line extension process, which reveal that the rail network’s growth is likely based on the nodes with the biggest lengths of the shortest path and that network protection should emphasize those nodes with the largest degrees and the highest betweenness values. This research may enhance the networkability of the rail system and better shape the future growth of public rail networks.
机译:近来,随着来自各个领域的学者分析交通网络,涉及交通中复杂网络应用的研究数量稳步增加。尽管如此,对铁路网络增长的研究相对很少。这项研究基于复杂网络理论研究了吉隆坡公共城市轨道交通网络(PURTNoKL)的演变,并涵盖了轨道系统的拓扑结构和网络增长的未来趋势。此外,还评估了面对不同攻击策略时的网络性能。考虑了三个拓扑网络特征:连接,集群和集中性。在PURTNoKL中,我们发现节点和边的总数显示出线性关系,并且平均度数保持在具有重尾分布的区间[2.0488,2.6774]之内。进化过程表明,度的累积概率分布(CPD)和平均最短路径长度分别与指数分布和正态分布都很好地拟合。此外,PURTNoKL表现出明显的团簇特征。大多数节点的值为2核心,中心点的紧密度和中间度的CPD分别服从正态分布函数和指数分布。最后,我们讨论了四种不同类型的网络增长方式和线路扩展过程,这表明铁路网络的增长很可能基于最短路径长度最大的节点,而网络保护应强调那些度数最大的节点。和最高的中间值。这项研究可以增强铁路系统的可联网性,并更好地塑造公共铁路网络的未来发展。

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