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arXiv 1509.04554physics.soc-phnlin.AO
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印度公交网络的统计分析

Statistical Analysis of Bus Networks in India

Atanu Chatterjee, Manju Manohar, Gitakrishnan Ramadurai

摘要:

在过去的十年中,网络科学领域已经成为跨学科研究的共同基础,这促使研究人员将几乎每个物理系统建模为由节点和链接组成的交互网络。虽然公共交通网络,如航空公司和铁路网络已被广泛研究,巴士网络的地位仍然是模糊的。在像印度这样的发展中国家,公交网络在日常通勤中发挥着重要作用,分析其拓扑结构并回答有关其演变,增长,鲁棒性和弹性的一些基本问题具有重要意义。在本文中,我们模拟印度主要城市的公交网络作为\textit{L}空间中的图形,并使用网络科学的概念来评估其各种统计特性。我们的分析揭示了一个广泛的网络拓扑结构与共同的小世界属性的基本特征。我们观察到,网络虽然,鲁棒性和弹性的随机攻击是特别的程度敏感。与现实世界的网络不同,如Internet,WWW和航空公司,它们是虚拟的,总线网络是物理约束的。各种地理和经济限制的存在使这些网络能够随着时间的推移而发展。因此,我们的研究结果揭示了这种地理和社会经济约束网络的演变,这将有助于我们在未来设计更有效的网络。

英文摘要:

Through the past decade the field of network science has established itself as a common ground for the cross-fertilization of exciting inter-disciplinary studies which has motivated researchers to model almost every physical system as an interacting network consisting of nodes and links. Although public transport networks such as airline and railway networks have been extensively studied, the status of bus networks still remains in obscurity. In developing countries like India, where bus networks play an important role in day-to-day commutation, it is of significant interest to analyze its topological structure and answer some of the basic questions on its evolution, growth, robustness and resiliency. In this paper, we model the bus networks of major Indian cities as graphs in \textit{L}-space, and evaluate their various statistical properties using concepts from network science. Our analysis reveals a wide spectrum of network topology with the common underlying feature of small-world property. We observe that the networks although, robust and resilient to random attacks are particularly degree-sensitive. Unlike real-world networks, like Internet, WWW and airline, which are virtual, bus networks are physically constrained. The presence of various geographical and economic constraints allow these networks to evolve over time. Our findings therefore, throw light on the evolution of such geographically and socio-economically constrained networks which will help us in designing more efficient networks in the future.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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