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Key Node Identification Method of Chengdu Metro Network Based on Comprehensive Assessment

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Advances in Smart Vehicular Technology, Transportation, Communication and Applications (VTCA 2018)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 129))

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Abstract

The identification of key nodes is conducive to improving the accuracy of network performance analysis. The topology of the Chengdu Metro Network (CMN) is analyzed based on complex network theory, a node importance evaluation index system including regional prosperity and node accessibility is constructed. Multi-comprehensive evaluation methods such as Relational Analysis, TOPSIS, Principal Components Analysis, Entropy Weight Method, etc., were used to rank 136 nodes. It is identified that 30 key nodes headed by East Chengdu Railway Station (56). At the same time, some starting, ending and intermediate stations with low degree or betweenness are equally important in urban rail transit network. Key precautions and maintenance are needed to ensure the normal operation of the CMN.

This research was supported by the National Key R&D Program of China (2017YFB1200702).

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Acknowledgement

This research was supported by the National Key R&D Program of China (2017YFB1200702).

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Authors and Affiliations

  1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, Sichuan, China

    Feng Xue, Chuan-Lei He, Zong-Sheng Sun & Xiao Yu

  2. National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu, 610031, Sichuan, China

    Feng Xue

Authors
  1. Feng Xue
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  2. Chuan-Lei He
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  3. Zong-Sheng Sun
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  4. Xiao Yu
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Corresponding author

Correspondence to Chuan-Lei He .

Editor information

Editors and Affiliations

  1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, Sichuan, China

    Shaoquan Ni

  2. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Tsu-Yang Wu

  3. School of Transportation, Fujian University of Technology, Fuzhou, Fujian, China

    Tang-Hsien Chang

  4. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

  5. University of Technology Sydney, Sydney, NSW, Australia

    Lakhmi C. Jain

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Xue, F., He, CL., Sun, ZS., Yu, X. (2019). Key Node Identification Method of Chengdu Metro Network Based on Comprehensive Assessment. In: Ni, S., Wu, TY., Chang, TH., Pan, JS., Jain, L. (eds) Advances in Smart Vehicular Technology, Transportation, Communication and Applications. VTCA 2018. Smart Innovation, Systems and Technologies, vol 129. Springer, Cham. https://doi.org/10.1007/978-3-030-04582-1_6

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