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Aggregating fuzzy implications to measure group consensus
conference contribution
posted on 2013-01-01, 00:00 authored by Gleb BeliakovGleb Beliakov, Simon JamesSimon James, T CalvoWe approach the problem of measuring consensus for a set of real inputs by aggregating the fuzzy implication degrees between each pair of inputs. We compare our operator with existing consensus measures in terms of their satisfaction of desirable properties. The appeal of such an approach lies in the interpretability and flexibility that results from component-wise construction which we modeled on the Bonferroni mean. We also outline some intentions for future research.
History
Event
Fuzzy Systems and NAFIPS. Joint World Congress and Annual Meeting (9th : 2013 : Edmonton, Alberta)Pagination
1016 - 1021Publisher
IEEELocation
Edmonton, AlbertaPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2013-06-24End date
2013-06-28ISBN-13
9781479903474Language
jpnPublication classification
E1 Full written paper - refereedCopyright notice
2013, IEEETitle of proceedings
IFSA/NAFIPS 2013 : Proceedings of the 9th Joint IFSA World Congress and NAFIPS Annual MeetingUsage metrics
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