• DocumentCode
    1795808
  • Title

    Fuzzy networks: What happens when fuzzy people are connected through social networks

  • Author

    Li-Xin Wang ; Mendel, Jerry M.

  • Author_Institution
    Dept. of Autom. Sci. & Technol., Xian Jiaotong Univ., Xian, China
  • fYear
    2014
  • fDate
    9-12 Dec. 2014
  • Firstpage
    30
  • Lastpage
    37
  • Abstract
    A fuzzy node is a fuzzy set whose membership function contains some uncertain parameters. Two fuzzy nodes are connected if the uncertain parameter of one node is provided by the fuzzy set from the other node. A fuzzy network is a connection of a number of fuzzy nodes. We define Gaussian Fuzzy Networks and study a number of basic connections in details, including basic center, basic standard deviation (sdv), basic center-sdv, chain-in-center, chain-in-sdv, self-feedback and some other connections. We derive the membership functions resulting from these connections that reveal how the fuzziness is propagated through the networks, and we explain what the mathematical results mean with respect to human behaviors.
  • Keywords
    Gaussian processes; fuzzy set theory; social networking (online); Gaussian fuzzy networks; basic center-sdv; basic standard deviation; chain-in-center; chain-in-sdv; fuzziness propagation; fuzzy node; fuzzy people; fuzzy set; human behaviors; membership functions; self-feedback; social networks; uncertain parameters; Bayes methods; Fuzzy sets; Network theory (graphs); Pragmatics; Social network services; Standards; Uncertainty; Social networks; fuzzy sets; human models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Foundations of Computational Intelligence (FOCI), 2014 IEEE Symposium on
  • Conference_Location
    Orlando, FL
  • Type

    conf

  • DOI
    10.1109/FOCI.2014.7007804
  • Filename
    7007804