Linguistic Aggregation Operators for Linguistic Decision Making Based on the Dempster-Shafer Theory of Evidence

نویسندگان

  • José M. Merigó
  • Montserrat Casanovas
  • Luis Martínez-López
چکیده

In this paper, we develop a new approach for decision making with Dempster-Shafer theory of evidence by using linguistic information. We suggest the use of different types of linguistic aggregation operators in the model. We then obtain as a result, the belief structure — linguistic ordered weighted averaging (BS-LOWA), the BS — linguistic hybrid averaging (BS-LHA) and a wide range of particular cases. Some of their main properties are studied. Finally, we provide an illustrative example that shows the different results obtained by using different types of linguistic aggregation operators in the new approach.

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عنوان ژورنال:
  • International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems

دوره 18  شماره 

صفحات  -

تاریخ انتشار 2010