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Classifying Large Graphs with Differential Privacy Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Estimating Unknown Values in Reciprocal Intuitionistic Preference Relations via Asymmetric Fuzzy Preference Relations

Authors : Francisco Chiclana, Raquel Ureña, Hamido Fujita, Enrique Herrera-Viedma

Published in: Modeling Decisions for Artificial Intelligence

Publisher: Springer International Publishing

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Abstract

Intuitionistic preference relations are becoming increasingly important in the field of group decision making since they present a flexible and simple way to the experts to provide their preference relations, while at the same time allowing them to accommodate a certain degree of hesitation inherent to all decision making processes. In this contribution, we prove the mathematical equivalence between the set of asymmetric fuzzy preference relations and the set of reciprocal intuitionistic fuzzy preference relations. This result is exploited to tackle the presence of incomplete reciprocal intuitionistic fuzzy preference relation in decision making by developing a consistency driven estimation procedure via the corresponding equivalent incomplete asymmetric fuzzy preference relation.

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previous chapter A Comparison of the GAI Model and the Choquet Integral w.r.t. a k-ary Capacity
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Metadata
Title
Estimating Unknown Values in Reciprocal Intuitionistic Preference Relations via Asymmetric Fuzzy Preference Relations
Authors
Francisco Chiclana
Raquel Ureña
Hamido Fujita
Enrique Herrera-Viedma
Copyright Year
2015
Book
Modeling Decisions for Artificial Intelligence

Print ISBN: 978-3-319-23239-3

Electronic ISBN: 978-3-319-23240-9

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-23240-9_6

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