Linguistic Pythagorean fuzzy sets and its applications in multiattribute decision‐making process
By Harish Garg. International Journal of Intelligent Systems, 2018
348 citations recorded by the source corpus.
In this article, a new linguistic Pythagorean fuzzy set (LPFS) is presented by combining the concepts of a Pythagorean fuzzy set and linguistic fuzzy set. LPFS is a better way to deal with the uncertain and imprecise information in decision making, which is characterized by linguistic membership and nonmembership degrees. Some of the basic operational laws, score, and accuracy functions are defined to compare the two or more linguistic Pythagorean fuzzy numbers and their properties are investigated in detail. Based on the norm operations, some series of the linguistic Pythagorean weighted averaging and geometric aggregation operators, named as linguistic Pythagorean fuzzy weighted average and geometric, ordered weighted average and geometric with linguistic Pythagorean fuzzy information are proposed. Furthermore, a multiattribute decision‐making method is established based on these operators. Finally, an illustrative example is used to illustrate the applicability and validity of the proposed approach and compare the results with the existing methods to show the effectiveness of it.
Subfields: Control and Systems Engineering, Management, Monitoring, Policy and Law, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/a7394d50675c39e4048292a34181345bbf077aad
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In Control and Systems Engineering
In Management, Monitoring, Policy and Law
In Management Science and Operations Research
Citations in the corpus
- Assessing occupational risks in pipeline construction using FMEA-based AHP-MOORA integrated approach under Pythagorean fuzzy environment (2019, background): “…2018b; 2017a; 2017b; Zhang and Xu 2014): b1 b2 if and only if lb1 lb2 and vb1 vb2 To compare the magnitude of two Pythagorean fuzzy numbers, a score function is developed by (Garg 2018a; 2018b; 2017a; 2017b; Zhang and Xu 2014) as follows: s b1ð Þ ¼ lb1ð Þ2 vb1ð Þ2 (7) Depending on the…”