• DocumentCode
    1852778
  • Title

    The Analysis of Knowledge Transfer Network Characteristic Based on Small-world Network Model

  • Author

    Bo, Yang ; Sheng-hua, XU

  • Author_Institution
    Sch. of Inf. Manage., Univ. of Finance & Econ., Nanchang, China
  • fYear
    2010
  • fDate
    22-24 Jan. 2010
  • Firstpage
    428
  • Lastpage
    432
  • Abstract
    By analysising Small-world Network Model and its algorithm, we adopt agent adaptability modeling method of Complex Adaptive System and use Multi-Agent development language Netlogo to build simulation model based on Knowledge Transfer Network of Small-world. We use the average path length of Small-world Network Characteristic and clustering coefficient to stand for AC frequency and aggregation degree between network organizations´ network nodes. Operating simulation model means Knowledge Transfer Network has evident Small-world Network Characteristic and confirms that under the condition of Small-world, the efficiency of Agent behavior and organization Knowledge Transfer can reach an upper high standard. It can offer theory director to construct adaptive knowledge communication between network organizations and changeable network construction.
  • Keywords
    adaptive systems; complex networks; knowledge management; multi-agent systems; Netlogo; adaptive knowledge communication; agent adaptability modeling method; complex adaptive system; knowledge transfer network characteristic; multiagent development; network organizations; small world network model; Adaptive systems; Algorithm design and analysis; Analytical models; Clustering algorithms; Complex networks; Finance; Information analysis; Information management; Knowledge transfer; Social network services; Knowledge Network; Multi-Agent Mod; NetLogo simulation; Small-World Netwok;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Future Networks, 2010. ICFN '10. Second International Conference on
  • Conference_Location
    Sanya, Hainan
  • Print_ISBN
    978-0-7695-3940-9
  • Electronic_ISBN
    978-1-4244-5667-3
  • Type

    conf

  • DOI
    10.1109/ICFN.2010.15
  • Filename
    5431805