• DocumentCode
    226497
  • Title

    A numerical two-scale model of multi-granularity linguistic variables and it´s application to group decision making

  • Author

    Mei Cai ; Xiuzhi Sang ; Xinwang Liu

  • Author_Institution
    Sch. of Econ. & Manage., Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    760
  • Lastpage
    767
  • Abstract
    Many group decision making (GDM) problems under uncertain environments have vague and imprecise information in linguistic variable formats. Multi-granularity linguistic method with the process of symbolic computation is a typical tool to solve such problems, and can be associated with the popular computing with words domain. In the paper, we present numerical two-scale model which is the extension of symbolic computation model. Firstly, numerical two-scale representation model is proposed with two scale measurements. One is used to reflect the order of linguistic variable and the other is used to model vagueness. Secondly, we give numerical two-scale computational model in group decision making. We discuss the rules of symbolic method which directly compute with the two numerical measurements. Finally, some aggregation operators are developed. The new model has the advantage of avoiding the vague information losing without adding the calculation difficulty.
  • Keywords
    distributed decision making; fuzzy set theory; mathematical operators; symbol manipulation; aggregation operators; group decision making; multigranularity linguistic method; multigranularity linguistic variables; numerical two-scale computational model; symbolic computation model; vague information lose; Computational modeling; Decision making; Educational institutions; Numerical models; Pragmatics; Semantics; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-2073-0
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2014.6891572
  • Filename
    6891572