Research on the Complexity Characteristics of Urban Metro Network Based on Complex Network Theory
Abstract
It is to provide decision support for later planning of metro network. Firstly, the space-L method is used to model the metro network topology. Secondly, four different indicators are used to analyze the complexity of metro network. The results show that the degree of metro network nodes in Xuzhou is generally low, and the degree distribution and power distribution are quite different. The network has no scale network properties. In Xuzhou metro network, the path between random station pairs is long, and the degree of node aggregation is low. There is a positive correlation between degree and betweenness, which can make more accurate importance assessment of the site.
Keywords
Full Text:
PDFReferences
Latora V, Marchiori M. Is the Boston subway a small-world network?[J]. Physica A: Statistical Mechanics and its Applications, 2002, 314(1–4): 109-113.
Gao J, Shi, QZ., Definition and evaluation modeling of metro network invulnerability[J]. Journal of railway, 2007(03): 29-33.
Ye Q., Vulnerability analysis of rail transit based on complex network theory[J]. China Safety Science Journal, 2012, 22(02): 122-126.
Yuan, J F, Li, QM, Jia RY, et al. Analysis of Operation Vulnerabilities of Urban Metro Network System [J]. China Safety Science Journal, 2012,22(05): 92-98.
Deng YL, Li, QM, Lu Y, et al. Topology vulnerability analysis and measure of urban metro net-work: The case of Nanjing[J]. Journal of Networks, 2013, 8(6): 1350−1356.
Wang, ZR, Li, QM, Liang, ZL. Evaluation of urban metro network topological structure vulnerability[J]. China Safety Science Journal, 2013, 23 (08): 114-119.
Zhang, TY, Song, R, Zheng, L, et al. Analysis of Domestic Subway Network Characteristic Based on Complex Network Theory[J]. Journal of Transport Information and Safety, 2012,30(05): 50-54.
Lai, LP. Research of Metro Networks Characteristics Based on complex network[J]. Natural Science Journal of Harbin Normal University, 2016,32(06): 30-33.
Zheng, SJ. Analysis of the topological structure of Shanghai metro network[J]. Intelligent Computers and Applications, 2019,9 (04): 205-208.
Barabas, AL, Albert, R. Emergence of scaling in random networks[J]. Science, 1999, 286:509-512.
Gao, TZ, Chen, KM, Li, FL. Topology analysis of urban metro transit network[J]. Journal of Chang'an University(Natural Science Edition), 2018, 38(03):97-106.
DOI: https://doi.org/10.18686/utc.v8i2.151
Refbacks
- There are currently no refbacks.
Copyright (c) 2022 Jiakun Wu
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.