TY - JOUR
T1 - Pythagorean fuzzy set
T2 - state of the art and future directions
AU - Peng, Xindong
AU - Selvachandran, Ganeshsree
N1 - Funding Information:
The authors are very appreciative to the reviewers for their precious comments which enormously ameliorated the quality of this paper. Our work is sponsored by the National Natural Science Foundation of China (No. 61462019), the General Project of Shaoguan University (No. SY2016KJ11).
Publisher Copyright:
© 2017, Springer Science+Business Media B.V., part of Springer Nature.
PY - 2019/10
Y1 - 2019/10
N2 - Pythagorean fuzzy set, generalized by Yager, is a new tool to deal with vagueness considering the membership grade μ and non-membership ν satisfying the condition μ2+ ν2≤ 1. It can be used to characterize the uncertain information more sufficiently and accurately than intuitionistic fuzzy set. Pythagorean fuzzy set has attracted great attention of many scholars that have been extended to new types and these extensions have been used in many areas such as decision making, aggregation operators, and information measures. Because of such a growth, we present an overview on Pythagorean fuzzy set with aim of offering a clear perspective on the different concepts, tools and trends related to their extension. In particular, we provide two novel algorithms in decision making problems under Pythagorean fuzzy environment. It may be served as a foundation for developing more algorithms in decision making.
AB - Pythagorean fuzzy set, generalized by Yager, is a new tool to deal with vagueness considering the membership grade μ and non-membership ν satisfying the condition μ2+ ν2≤ 1. It can be used to characterize the uncertain information more sufficiently and accurately than intuitionistic fuzzy set. Pythagorean fuzzy set has attracted great attention of many scholars that have been extended to new types and these extensions have been used in many areas such as decision making, aggregation operators, and information measures. Because of such a growth, we present an overview on Pythagorean fuzzy set with aim of offering a clear perspective on the different concepts, tools and trends related to their extension. In particular, we provide two novel algorithms in decision making problems under Pythagorean fuzzy environment. It may be served as a foundation for developing more algorithms in decision making.
KW - Aggregation operators
KW - Decision making
KW - Information measures
KW - Intuitionistic fuzzy set
KW - Pythagorean fuzzy set
UR - https://www.scopus.com/pages/publications/85035751183
U2 - 10.1007/s10462-017-9596-9
DO - 10.1007/s10462-017-9596-9
M3 - Article
AN - SCOPUS:85035751183
SN - 0269-2821
VL - 52
SP - 1873
EP - 1927
JO - Artificial Intelligence Review
JF - Artificial Intelligence Review
IS - 3
ER -