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General Information
    • ISSN: 1793-8236 (Online)
    • Abbreviated Title Int. J. Eng. Technol.
    • Frequency:  Quarterly 
    • DOI: 10.7763/IJET
    • APC: 500 USD
    • Managing Editor: Ms. Jennifer Zeng
    • Abstracting/ Indexing: Inspec (IET), CNKI Google Scholar, EBSCO, ProQuest, Crossref, Ulrich Periodicals Directory, Chemical Abstracts Services (CAS), etc.
    • E-mail: ijet_Editor@126.com
Editor-in-chief
IJET 2014 Vol.6(6): 459-464 ISSN: 1793-8236
DOI: 10.7763/IJET.2014.V6.741

Evaluating the Node Importance in Lifeline Systems Based on Variable Fuzzy Clustering

Mingyuan Zhang and Shisen Feng

Abstract—Under disasters, the destruction of some key nodes in the lifeline system generally leads to the entire disastrous consequence. In order to increase the reliability of lifeline network by protecting the key nodes in network, the paper proposes a method to identify the key nodes in lifeline systems by evaluating the node importance based on variable fuzzy clustering. The paper takes water supply network system as an example and establishes the node importance evaluation indices considering both network topology and resource supply factors. The variable fuzzy clustering method is adopted for cluster analysis of nodes in a case study demonstrated. And the results show that the key nodes in water supply network can be objectively identified by variable fuzzy clustering method. This methodology can help decision makers who work on disaster prevention and reduction of urban lifeline system to build the effective disaster prevention plans.

Index Terms—Lifeline system, node importance, variable fuzzy clustering, network topology, resources supply.

Mingyuan Zhang is with the Dalian University of Technology, Liaoning, China (e-mail: myzhang@ dlut.edu.cn).
Shisen Feng is with the Industry Section, Development Research Centre of Dalian People’s Government, Dalian, China (e-mail: shisen_80@126. com).

[PDF]

Cite: Mingyuan Zhang and Shisen Feng, "Evaluating the Node Importance in Lifeline Systems Based on Variable Fuzzy Clustering," International Journal of Engineering and Technology vol. 6, no. 6, pp. 459-464, 2014.

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