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FACTORIZATION OF INTUITIONISTIC FUZZY PREFERENCE RELATIONS [PDF]

New Mathematics and Natural Computation, 2014
The proofs of many factorization results for an intuitionistic fuzzy binary relation 〈ρμ,ρν〉 involve dual proofs, one for ρμ with respect to a t-conorm ⊕ and one for ρν with respect to a t-norm ⊗. In this paper, we show that one proof can be obtained from the other by considering ⊕ and ⊗ dual under an involutive fuzzy complement.
JOHN N. MORDESON, TERRY D. CLARK, KAREN ALBERT   +2 more
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Intuitionistic fuzzy preference relations

Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011), 2011
We consider properties of intuitionistic fuzzy preference relations. We study preservation of a preference relation by lattice operations, composition and some Atanassov’s operators like F, , P, , Q, , where , 2 [0,1]. We also define semi-properties of intuitionistic fuzzy relations, namely reflexivity, irreflexivity, connectedness, asymmetry ...
Barbara Pekala, Urszula Dudziak
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Transitivity measurements of fuzzy preference relations

Fuzzy Sets and Systems, 2021
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Fang Liu, Shu-Cai Zou, Qi-Rui You
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Fuzzy preference relation rough sets

2008 IEEE International Conference on Granular Computing, 2008
Preference analysis is a class of important tasks in multi-criteria decision making. The classical rough set theory was generalized to deal with preference analysis by replacing equivalence relations with dominance relation. However, crisp preference relations can not reflect the fuzziness in criteria. In this paper, we introduce the logsig function to
null Qinghua Hu, null Daren Yu, null Congxin Wu   +2 more
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Incomplete hesitant fuzzy preference relation

Journal of Statistics and Management Systems, 2018
In the process of decision making, a decision maker may give her/his judgments using hesitant fuzzy preference relations for hesitancy and uncertainty. Limitations of the experts’ professional knowledge, experience, and lack of time may lead to preferences in hesitant fuzzy preference relation(HFPR) which are usually incomplete. Zhang et al.
Mamata Sahu, Anjana Gupta
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Intuitionistic Fuzzy Preference Relations

2012
In any fuzzy preference relation (FPR), each element denotes the membership degree of how one decision alternative is preferred to another. The values of these elements range between 0 and 1. This key idea originates from Zadeh’s concept of fuzzy sets (Zadeh, 1965).
Zaiwu Gong, Yi Lin, Tianxiang Yao
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Dynamic Fuzzy Preference Relations

Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 2007
In this paper, we present a class of new preference relations-dynamic fuzzy preference relations in which all the elements are the variables of time, and study some of their desirable properties. We also give a straightforward method for deriving the priority weights of dynamic fuzzy preference relations, and then develop an approach to constructing ...
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Argumentation Framework with Fuzzy Preference Relations

2010
Dung's argumentation developed in Artificial Intelligence is based on a binary attack relation. An important particular case arises when there is a Boolean preference relation between the arguments. We propose to extend this argumentation framework to a fuzzy preference relation. This implies that an argument can attack another one to a certain degree.
Kaci, Souhila, Labreuche, Christophe
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On fuzzy preference relations

International Journal of Intelligent Systems, 1991
Summary: Triangular norms, conorms, and negation functions are used as interpretations for propositional connectives in a multiple-valued logic model for fuzzy binary relations of weak preference, strict preference, and indifference. It is shown that the Law of Contradiction is a necessary condition for the very existence of reflexive transitive fuzzy ...
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Aggregation of I-transitive fuzzy relations and fuzzy preference relations

Computational and Applied Mathematics
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Li, Dechao, Yao, Yutao
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