Analysis of Social Networks by Using Pythagorean Cubic Fuzzy Einstein Weighted Geometric Aggregation Operators | Zendy

Tehreem Tehreem | Zendy; Amjad Hussain | Zendy; Jung Rye Lee | Zendy; Madad Khan | Zendy; Dong Yun Shin | Zendy

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Analysis of Social Networks by Using Pythagorean Cubic Fuzzy Einstein Weighted Geometric Aggregation Operators

Author(s) -

Tehreem Tehreem,

Amjad Hussain,

Jung Rye Lee,

Madad Khan,

Dong Yun Shin

Publication year - 2021

Publication title -

journal of mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.252

H-Index - 13

eISSN - 2314-4785

pISSN - 2314-4629

DOI - 10.1155/2021/5516869

Subject(s) - pythagorean theorem , mathematics , einstein , operator (biology) , fuzzy logic , set (abstract data type) , fuzzy set , algebra over a field , algorithm , artificial intelligence , computer science , pure mathematics , geometry , biochemistry , chemistry , repressor , mathematical physics , gene , programming language , transcription factor

Pythagorean cubic set (PCFS) is the combination of the Pythagorean fuzzy set (PFS) and interval-valued Pythagorean fuzzy set (IVPFS). PCFS handle more uncertainties than PFS and IVPFS and thus are more extensive in their applications. The objective of this paper is under the PCFS to establish some novel operational laws and their corresponding Einstein weighted geometric aggregation operators. We describe some novel Pythagorean cubic fuzzy Einstein weighted geometric (PCFEWG) operators to handle multiple attribute group decision-making problems. The desirable relationship and the characteristics of the proposed operator are discussed in detail. Finally, a descriptive case is given to describe the practicality and the feasibility of the methodology established.

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