Results 211 to 220 of about 142,339 (277)
Novel concept of linguistic fractional fuzzy information for effective water filtration decision-making problem based on WASPAS method. [PDF]
Sci RepAbdullah S, Ali H, Rahimzai AA, Khan S.
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IEEE transactions on fuzzy systems, 2023
For the first time, the critical worldwide problem of prioritizing zero-emission last-mile delivery (LMD) solutions for sustainable city logistics is addressed and solved in this article.
A. Saha +4 more
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For the first time, the critical worldwide problem of prioritizing zero-emission last-mile delivery (LMD) solutions for sustainable city logistics is addressed and solved in this article.
A. Saha +4 more
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Scores for Hesitant Fuzzy Sets: Aggregation Functions and Generalized Integrals
IEEE transactions on fuzzy systems, 2023There are several extensions of fuzzy sets. Hesitant fuzzy sets are one of them. They are defined in terms of a set of membership degrees. For a typical hesitant fuzzy set, this set of membership degrees has a finite number of values.
Y. Narukawa, V. Torra
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A Lattice Structure on Hesitant Fuzzy Sets
IEEE Transactions on Fuzzy Systems, 2023“Marı́a de Maeztu” Excellence Unit IMAG, reference CEX2020-001105-M, funded by MCIN/AEI/10.13039/501100011033/
Pascual Jara +3 more
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International Journal of Intelligent Systems, 2022
A dual hesitant fuzzy set (DHFS) describes the uncertainty in the real world by using the membership degree and nonmembership degree. It can collect fuzzy information comprehensively and apply them into decision‐making tasks efficiently. In this article,
Wenyi Zeng +5 more
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A dual hesitant fuzzy set (DHFS) describes the uncertainty in the real world by using the membership degree and nonmembership degree. It can collect fuzzy information comprehensively and apply them into decision‐making tasks efficiently. In this article,
Wenyi Zeng +5 more
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Journal of Intelligent & Fuzzy Systems, 2021
Fuzzy set (FS) theory is one of the most important tool to deasl with complicated and difficult information in real-world. Now FS has many extensions and hesitant fuzzy set (HFS) is one of them.
Tahir Mahmood +3 more
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Fuzzy set (FS) theory is one of the most important tool to deasl with complicated and difficult information in real-world. Now FS has many extensions and hesitant fuzzy set (HFS) is one of them.
Tahir Mahmood +3 more
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International Journal of Intelligent Systems, 2017
The hesitant fuzzy sets are a new efficient mathematical approach to study imprecise, uncertain, or incomplete knowledge. This paper focuses to extend this approach on a lattice and shows that two large application concepts of the fuzzy set theory namely resolution identity and representation theorem are true under this extended definition.
Alireza Hosseini Dehmiry +3 more
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The hesitant fuzzy sets are a new efficient mathematical approach to study imprecise, uncertain, or incomplete knowledge. This paper focuses to extend this approach on a lattice and shows that two large application concepts of the fuzzy set theory namely resolution identity and representation theorem are true under this extended definition.
Alireza Hosseini Dehmiry +3 more
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On hesitant fuzzy sets and decision
2009 IEEE International Conference on Fuzzy Systems, 2009Intuitionistic Fuzzy Sets (IFS) are a generalization of fuzzy sets where the membership is an interval. That is, membership, instead of being a single value, is an interval. A large number of operations have been defined for this type of fuzzy sets, and several applications have been developed in the last years. In this paper we describe hesitant fuzzy
Yasuo Narukawa, Vicenç Torra
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Journal of Intelligent & Fuzzy Systems, 2016
Convex hesitant fuzzy sets are define as an extension of convex fuzzy sets. Also level sets are defined for hesitant fuzzy sets and discussed with their convexity. We focus on aggregation functions for hesitant fuzzy elements. These aggregation functions are further extended for hesitant fuzzy sets as well as for the convex structures of these sets.
Ismat Beg, Tabasam Rashid
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Convex hesitant fuzzy sets are define as an extension of convex fuzzy sets. Also level sets are defined for hesitant fuzzy sets and discussed with their convexity. We focus on aggregation functions for hesitant fuzzy elements. These aggregation functions are further extended for hesitant fuzzy sets as well as for the convex structures of these sets.
Ismat Beg, Tabasam Rashid
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Information Systems on Hesitant Fuzzy Sets
International Journal of Rough Sets and Data Analysis, 2016Knowledge extraction from information systems is one of the most significant problems in artificial intelligence. This paper attempts to study information systems in the hesitant fuzzy domain. It studies information systems which has a set of possible membership values. Illustration of a case is provided where the hesitant membership values are arrived
Sunil Jacob John, D. Deepak
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