A complex network based model for detecting isolated communities in water distribution networks

被引:12
|
作者
Sheng, Nan [1 ]
Jia, Youwei [2 ]
Xu, Zhao [2 ]
Ho, Siu-Lau [2 ]
Kan, Chi Wai [3 ]
机构
[1] Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong, Hong Kong, Peoples R China
[2] Hong Kong Polytech Univ, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China
[3] Hong Kong Polytech Univ, Inst Text & Clothing, Hong Kong, Hong Kong, Peoples R China
关键词
INTERDEPENDENT INFRASTRUCTURE SYSTEMS; VULNERABILITY ANALYSIS; FINDING COMMUNITIES; POWER; RESILIENCE; TRANSITION;
D O I
10.1063/1.4823803
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Water distribution network (WDN) is a typical real-world complex network of major infrastructure that plays an important role in human's daily life. In this paper, we explore the formation of isolated communities in WDN based on complex network theory. A graph-algebraic model is proposed to effectively detect the potential communities due to pipeline failures. This model can properly illustrate the connectivity and evolution of WDN during different stages of contingency events, and identify the emerging isolated communities through spectral analysis on Laplacian matrix. A case study on a practical urban WDN in China is conducted, and the consistency between the simulation results and the historical data are reported to showcase the feasibility and effectiveness of the proposed model. (C) 2013 AIP Publishing LLC.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] A hybrid artificial immune network for detecting communities in complex networks
    Karimi-Majd, Amir-Mohsen
    Fathian, Mohammad
    Amiri, Babak
    COMPUTING, 2015, 97 (05) : 483 - 507
  • [2] A hybrid artificial immune network for detecting communities in complex networks
    Amir-Mohsen Karimi-Majd
    Mohammad Fathian
    Babak Amiri
    Computing, 2015, 97 : 483 - 507
  • [3] Algorithm for Detecting Communities in Complex Networks Based on Hadoop
    Hai, Mo
    Li, Haifeng
    Ma, Zhekun
    Gao, Xiaomei
    SYMMETRY-BASEL, 2019, 11 (11):
  • [4] A Stochastic Model for Detecting Heterogeneous Link Communities in Complex Networks
    He, Dongxiao
    Liu, Dayou
    Jin, Di
    Zhang, Weixiong
    PROCEEDINGS OF THE TWENTY-NINTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2015, : 130 - 136
  • [5] A focused crawling method based on detecting communities in complex networks
    ShenGui-Lan
    Jie, Sun
    Xiao-Ping, Yang
    International Journal of Smart Home, 2015, 9 (08): : 187 - 196
  • [6] Detecting multi-path based communities in complex networks
    Ren, Lin
    Zhou, Guo-Hua
    International Journal of Applied Mathematics and Statistics, 2013, 48 (18): : 263 - 271
  • [7] Detecting overlapping communities based on vital nodes in complex networks
    王兴元
    王宇
    秦小蒙
    李睿
    Justine Eustace
    Chinese Physics B, 2018, 27 (10) : 256 - 263
  • [8] Detecting overlapping communities based on vital nodes in complex networks
    Wang, Xingyuan
    Wang, Yu
    Qin, Xiaomeng
    Li, Rui
    Eustace, Justine
    CHINESE PHYSICS B, 2018, 27 (10)
  • [9] Detecting Overlapping Communities Based on Community Cores in Complex Networks
    Shang Ming-Sheng
    Chen Duan-Bing
    Zhou Tao
    CHINESE PHYSICS LETTERS, 2010, 27 (05)
  • [10] Detecting susceptible communities and individuals in hospital contact networks: a model based on social network analysis
    Yang, Yixuan
    Peng, Sony
    Siet, Sophort
    Ilkhomjon, Sadriddinov
    Vilakone, Phonexay
    Kim, Seok-Hoon
    Park, Doo-Soon
    CONNECTION SCIENCE, 2023, 35 (01)