Complex Sciences. First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009, Revised Papers, Part 2

Research Article

Community Structure Detection in Complex Networks with Applications to Gas-Liquid Two-Phase Flow

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  • @INPROCEEDINGS{10.1007/978-3-642-02469-6_68,
        author={Zhongke Gao and Ningde Jin},
        title={Community Structure Detection in Complex Networks with Applications to Gas-Liquid Two-Phase Flow},
        proceedings={Complex Sciences. First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009, Revised Papers, Part 2},
        proceedings_a={COMPLEX PART 2},
        year={2012},
        month={5},
        keywords={complex networks community structure detection data field theory two-phase flow pattern identification},
        doi={10.1007/978-3-642-02469-6_68}
    }
    
  • Zhongke Gao
    Ningde Jin
    Year: 2012
    Community Structure Detection in Complex Networks with Applications to Gas-Liquid Two-Phase Flow
    COMPLEX PART 2
    Springer
    DOI: 10.1007/978-3-642-02469-6_68
Zhongke Gao1,*, Ningde Jin1
  • 1: Tianjin University
*Contact email: gaozhongke_1982@163.com

Abstract

We propose an algorithm to detect community structure in complex networks based on data field theory. The efficiency and accuracy of the algorithm for computer-simulated and real networks make it feasible to be used for the accurate detection of community structure in complex networks. Using the conductance fluctuating signals measured from gas-liquid two-phase flow dynamic experiments, we construct the flow pattern complex network. With the applications of the community-detection algorithm to the flow pattern complex network, we achieve good identification of flow pattern in gas-liquid two-phase flow. In this paper, from a new perspective, we not only present a new community-detection algorithm based on data field theory, but also build a bridge between complex network and two-phase flow.