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A Directional Evolution Control Model for Network

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Intelligent Computing Theories and Methodologies (ICIC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9226))

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Abstract

In order to control the evolution direction of network to achieve certain goals, we proposed Directional Evolution Control Model for Network Based on Percolation Coefficient (PC-DECMN). Firstly, after the analysis of the spreading behavior based on SI model, we found that the influence scope was only related to the topology structure of network and initial source of infection. So the definition of percolation coefficient to measure the influence scope was proposed based on the transfer closure of adjacency matrix. Then, PC-DECMN was established based on the definition of percolation coefficient. Simulation experiment using the guarantee data of certain financial institution shows that, PC-DECMN can effectively control the evolution of guarantee network so that it can resist the risk better, compared with the natural evolved guarantee network.

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Author information

Authors and Affiliations

  1. College of Engineer and Information Technology, University of Chinese Academy of Sciences, Yu Quan Road 19A, Shi Jing Shan District, Beijing, 100049, China

    Gang Luo & Yawei Zhao

Authors
  1. Gang Luo
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  2. Yawei Zhao
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Corresponding author

Correspondence to Yawei Zhao .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

  3. Liverpool John Moores University, Liverpool, United Kingdom

    Abir Hussain

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© 2015 Springer International Publishing Switzerland

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Luo, G., Zhao, Y. (2015). A Directional Evolution Control Model for Network. In: Huang, DS., Jo, KH., Hussain, A. (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in Computer Science(), vol 9226. Springer, Cham. https://doi.org/10.1007/978-3-319-22186-1_7

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  • DOI: https://doi.org/10.1007/978-3-319-22186-1_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22185-4

  • Online ISBN: 978-3-319-22186-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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