• DocumentCode
    3431933
  • Title

    Contracting community for computing maximum flow

  • Author

    Zhang, YanPing ; Xu, Xiansheng ; Hua, Bo ; Zhao, Shu

  • Author_Institution
    School of Computer Science and Technology, Anhui University, Hefei, 230039, China
  • fYear
    2012
  • fDate
    11-13 Aug. 2012
  • Firstpage
    651
  • Lastpage
    656
  • Abstract
    In this paper, we propose a novel method named Contracting Community Approach (CCA) to get the maximum flow of flow network. Firstly, we contract communities in the original network. Then, we apply classic algorithms on the contracted network to approximately solve the maximum flow problem. Experimental results show that the efficiency of the proposed algorithm. For sparse networks, the size of network is reduced to 58.38% averagely and the correctness of maximum flow is over 95%. For middle dense networks, the size of network is reduced to 65.77% averagely. For dense networks, the size of network is reduced to 64.84% averagely. And the correctness of maximum flow even reach 100% both in many middle dense and dense cases in our experiments.
  • Keywords
    Artificial neural networks; Educational institutions; Video recording; community; contracting; maximum flow; network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing (GrC), 2012 IEEE International Conference on
  • Conference_Location
    Hangzhou, China
  • Print_ISBN
    978-1-4673-2310-9
  • Type

    conf

  • DOI
    10.1109/GrC.2012.6468649
  • Filename
    6468649