Semantic Scholar Open Access 2018 232 sitasi

Pythagorean Fuzzy Maclaurin Symmetric Mean Operators in Multiple Attribute Decision Making

G. Wei Mao Lu

Lihat Sumber DOI

Abstrak

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.

Topik & Kata Kunci

Computer Science Mathematics

Penulis (2)

G. Wei

Mao Lu

Format Sitasi

APA MLA BibTeX

Wei, G., Lu, M. (2018). Pythagorean Fuzzy Maclaurin Symmetric Mean Operators in Multiple Attribute Decision Making. https://doi.org/10.1002/int.21911

Akses Cepat

Lihat di Sumber doi.org/10.1002/int.21911

Informasi Jurnal

Tahun Terbit: 2018
Bahasa: en
Total Sitasi: 232×
Sumber Database: Semantic Scholar
DOI: 10.1002/int.21911
Akses: Open Access ✓