Premium
Pythagorean Fuzzy Maclaurin Symmetric Mean Operators in Multiple Attribute Decision Making
Author(s) -
Wei Guiwu,
Lu Mao
Publication year - 2018
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21911
Subject(s) - pythagorean theorem , operator (biology) , fuzzy logic , mathematics , weighted arithmetic mean , generalized mean , algebra over a field , computer science , artificial intelligence , pure mathematics , statistics , geometry , biochemistry , chemistry , repressor , transcription factor , gene
Abstract The Maclaurin symmetric mean (MSM) operator is a classical mean type aggregation operator used in modern information fusion theory, which is suitable to aggregate numerical values. The prominent characteristic of the MSM operator is that it can capture the interrelationship among the multiinput arguments. In this paper, we extend MSM to Pythagorean fuzzy environment to propose the Pythagorean fuzzy Maclaurin symmetric mean and Pythagorean fuzzy weighted Maclaurin symmetric mean operators. Then, some desirable properties and special cases of these operators are discussed in detail. Finally, a numerical example is provided to illustrate the feasibility of the proposed methods and deliver a comparative analysis.