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A new method to rank fuzzy numbers using Dempster-Shafer theory with fuzzy targets

Chai, Kok Chin, Tay, Kai Meng and Lim, Chee Peng 2016, A new method to rank fuzzy numbers using Dempster-Shafer theory with fuzzy targets, Information sciences, vol. 346-347, pp. 302-317, doi: 10.1016/j.ins.2016.01.066.

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Title A new method to rank fuzzy numbers using Dempster-Shafer theory with fuzzy targets
Author(s) Chai, Kok Chin
Tay, Kai Meng
Lim, Chee PengORCID iD for Lim, Chee Peng orcid.org/0000-0003-4191-9083
Journal name Information sciences
Volume number 346-347
Start page 302
End page 317
Total pages 16
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2016-06-10
ISSN 0020-0255
Keyword(s) Dempster–Shafer theory
Fuzzy ranking
Fuzzy targets
Murphy’s combination rule
Transferable Belief Model
Summary In this paper, an extended ranking method for fuzzy numbers, which is a synthesis of fuzzy targets and the Dempster-Shafer Theory (DST) of evidence, is devised. The use of fuzzy targets to reflect human viewpoints in fuzzy ranking is not new. However, different fuzzy targets can lead to contradictory fuzzy ranking results; making it difficult to reach a final decision. In this paper, the results from different viewpoints are treated as different sources of evidence, and Murphy's combination rule is used to aggregate the fuzzy ranking results. DST allows fuzzy numbers to be compared and ranked while preserving their uncertain and imprecise characteristics. In addition, a hybrid method consisting of fuzzy targets and DST with the Transferable Belief Model is formulated, which fulfils a number of important ordering properties. A series of empirical experiments with benchmark examples has been conducted and the experimental results clearly indicate the usefulness of the proposed method.
Language eng
DOI 10.1016/j.ins.2016.01.066
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, Elsevier
Persistent URL http://hdl.handle.net/10536/DRO/DU:30083089

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
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