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ArticleConsensus measures constructed from aggregation functions and fuzzy implications

Gleb Beliakov2013

Article2013

Consensus measures constructed from aggregation functions and fuzzy implications

Gleb Beliakov · Tomasa Calvo · Simon James

72 citations·0/0 files stored·Knowledge-Based Systems

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Multi-Criteria Decision Making Advanced Algebra and Logic Fuzzy and Soft Set Theory

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References

2007Aggregation Functions: A Guide for Practitioners 1996A model of consensus in group decision making under linguistic assessments 2002A consensus model for multiperson decision making with different preference structures 2007A Consensus Model for Group Decision Making With Incomplete Fuzzy Preference Relations 2005A Consensus Support System Model for Group Decision-Making Problems With Multigranular Linguistic Preference Relations 2007Modeling Decisions: Information Fusion and Aggregation Operators 1992Group decision making and consensus under fuzzy preferences and fuzzy majority 2012A statistical comparative study of different similarity measures of consensus in group decision making

Cited by

2019Balance Dynamic Clustering Analysis and Consensus Reaching Process With Consensus Evolution Networks in Large-Scale Group Decision Making 2016On the definition of penalty functions in data aggregation 2015Decision complexity and consensus in Web-based spatial decision making: A case study of site selection problem using GIS and multicriteria analysis 2020Linear uncertain extensions of the minimum cost consensus model based on uncertain distance and consensus utility

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Details

Year2013

Typearticle

Published2013-07-17

VenueKnowledge-Based Systems

ISSN-L0950-7051

Languageen

Citations72

Files0 public / 0

ShelfMulti-Criteria Decision Making

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doi10.1016/j.knosys.2013.07.002

openalex_workW1969696992

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2022Relationship between the distance consensus and the consensus degree in comprehensive minimum cost consensus models: A polytope-based analysis

2020Collaborative spatial multicriteria evaluation: a review and directions for future research

2021Strategies on admissible total orders over typical hesitant fuzzy implications applied to decision making problems