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Zeshui Xu

Researcher at Sichuan University

Publications -  849
Citations -  60364

Zeshui Xu is an academic researcher from Sichuan University. The author has contributed to research in topics: Fuzzy logic & Fuzzy set. The author has an hindex of 113, co-authored 752 publications receiving 48543 citations. Previous affiliations of Zeshui Xu include Nanjing University of Information Science and Technology & Nanjing University of Science and Technology.

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Intuitionistic Fuzzy Aggregation Operators

TL;DR: Based on score function and accuracy function, a method is introduced for the comparison between two intuitionistic fuzzy values and some aggregation operators are developed, such as the intuitionism fuzzy weighted averaging operator, intuitionists fuzzy ordered weighted averaging operators, and intuitionistic fuzziness hybrid aggregation operator, for aggregating intuitionist fuzzy values.
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Some geometric aggregation operators based on intuitionistic fuzzy sets

TL;DR: This paper develops some new geometric aggregation operators, such as the intuitionistic fuzzy weighted geometric (IFWG) operator, the intuitionists fuzzy ordered weighted geometric(IFOWG)operator, and the intuitionism fuzzy hybrid geometric (ifHG) operators, which extend the WG and OWG operators to accommodate the environment in which the given arguments are intuitionistic fuzz sets.
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Hesitant fuzzy information aggregation in decision making

TL;DR: The relationship between intutionistic fuzzy set and hesitant fuzzy set is discussed, based on which some operations and aggregation operators for hesitant fuzzy elements are developed and their application in solving decision making problems is given.
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Extension of TOPSIS to Multiple Criteria Decision Making with Pythagorean Fuzzy Sets

TL;DR: Some novel operational laws of PFSs are defined and an extended technique for order preference by similarity to ideal solution method is proposed to deal effectively with them for the multicriteria decision‐making problems with PFS.
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Distance and similarity measures for hesitant fuzzy sets

TL;DR: A variety of distance measures for hesitant fuzzy sets are proposed, based on which the corresponding similarity measures can be obtained and can alleviate the influence of unduly large deviations on the aggregation results by assigning them low (or high) weights.