Evidential reasoning with linguistic belief structures

Huchang Liao, Ran Fang*, Jian Bo Yang, Dong Ling Xu

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

The Evidential Reasoning (ER) approach is an inference method to analyse multi-criteria decision-making problems with uncertainties. However, due to the pressure of time, limit of knowledge and lack of data, such problems need to be assessed using both human judgments and limited data. In this case, it is suitable to provide a belief structure by means of linguistic terms, which we refer to as linguistic belief structure. Considering that different decision-makers may have different perceptions, the semantics of human judgments can also be different. In this paper, we introduce three linguistic scale functions to capture the semantics of linguistic belief degrees for constructing a complete linguistic information fusion method. We then extend the framework of the ER approach to multi-expert multi-criteria decision making. The method proposed in this study can fill the research gap of the ER approach for multi-expert multi-criteria decision-making problems with linguistic belief structures.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Fuzzy Systems, FUZZ 2019
PublisherIEEE
ISBN (Electronic)9781538617281
DOIs
Publication statusE-pub ahead of print - 10 Oct 2019
Event2019 IEEE International Conference on Fuzzy Systems, FUZZ 2019 - New Orleans, United States
Duration: 23 Jun 201926 Jun 2019

Publication series

NameIEEE International Conference on Fuzzy Systems
Volume2019-June
ISSN (Print)1098-7584

Conference

Conference2019 IEEE International Conference on Fuzzy Systems, FUZZ 2019
Country/TerritoryUnited States
CityNew Orleans
Period23/06/1926/06/19

Keywords

  • Evidential reasoning
  • linguistic belief structure
  • linguistic scale function
  • multi-expert multi-criteria decision making

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