Picture Fuzzy Operators with Application in Pattern Recognition
DOI:
https://doi.org/10.26713/cma.v17i1.3541Abstract
In our daily lives, we are to face many uncertain situations where vague or imprecise data are the robust issue for consideration. Conducting these imprecise data is more tough job than precise data. Picture fuzzy set is one of the powerful concept to deal with these kinds of imprecise data effectively because of its diverse operations techniques in several dimensions. In this article, different sorts of operators for picture fuzzy sets are defined and various related properties of these operators are explored. Some mean operators in particular cases are discussed with some of their associated properties. Finally, a real life application is described in make decision.
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A.H. Ganie et al.,Some new correlation coefficients of picture fuzzy sets with applications. Neural Computing and Applications, (2020), https://doi.org/10.1007/s00521-020-04715-y(0123456789.
A. Si, S. Das and S. Kar, An Approach To Rank Picture Fuzzy Numbers For Decision Making Problems, Decision Making: Applications in Management and Engineering 2(2) (2019), 54-64.
B.C. Cuong, Picture Fuzzy Sets. Journal of Computer Science and Cybernetics 30(4) (2014), 409-420.
B.C. Cuong B.C. and V. Kreinovich, Picture Fuzzy Sets- a new concept for computational intelligence problems, in: Proceedings of the Third World Congress on Information and Communication Technologies WIICT, (2013), 1– 6.
C. Jana et.al., Picture fuzzy Dombi aggregation operators: Application to MADM process. Appl Soft Comput, 74(2019), 99–109.
C. Tian et al., Weighted picture fuzzy aggregation operators and their applications to multi-criteria decision-making problems, Comput. Industr. Eng. 137(2019), 10 - 37.
C. Wang, Some geometric aggregation operators based on picture fuzzy sets and their applications in multiple attribute decision making, Italian J Pure Appl Math, 37(2017), 477–92.
G. Wei, Picture fuzzy cross-entropy for multiple attribute decision making problems, Journal of Business Economics and Management ,17(2016), 491–502.
G. Wei, Picture fuzzy aggregation operator and their application to multiple attribute decision making, Journal of Intelligent & Fuzzy Systems, 33(2017), 713–724.
G. Wei, Picture fuzzy Hamacher aggregation operators and their application to multiple attribute decision making, Fundamenta Informaticae, 157(2018), 271–320.
H. Garg, Some Picture Fuzzy Aggregation Operators and Their Applications to Multicriteria Decision-Making, Arab. J. Sci. Eng., 42(2017), 5275–5290.
K.T. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets and System, 20(1986), 87–96.
K.T. Atanassov, Intuitionistic Fuzzy Sets: Theory and Applications. Springer-Verlag Berlin Heidelberg GmbH, (1999).
L. A. Zadeh, Fuzzy sets, Inform. Control, 8(1965), 338-353.
L.H. Son, Measuring analogousness in picture fuzzy sets: from picture distance measures to picture association measures, Fuzzy Optim Decis Making, (2016), DOI 10.1007/s10700-016-9249-5.
L.H Son, Picture inference system: A new fuzzy inference system on picture fuzzy set, Appl. Intell. 46(2017), 652–669.
L. Minxia, Picture Fuzzy Geometric Aggregation Operators Based on a Trapezoidal Fuzzy Number and Its Application, Symmetry, 13(2021), 119. https:// doi.org/10.3390/sym13010119
M.J. Khan et. al., Bi-parametric distance and similarity measures of picture fuzzy sets and their applications in medical diagnosis, Egyptian Informatics Journal 22(2021), 201–212.
M.K. Hasan et al., Some Picture Fuzzy Mean Operators and Their Applications in Decision-Making, J. Fuzzy. Ext. Appl. 3(4) (2022), 349–361.
M. Luo and Y. Zhang, A new similarity measure between picture fuzzy sets and its application, Engineering Applications of Artificial Intelligence, (2020), https://doi.org/10.1016/j.engappai.2020.103956.
M. Qiyas et al., Utilizing linguistic picture fuzzy aggregation operators for multiple-attribute decision-making problems, Int J Fuzzy Syst, 22(1) (2020), 310–20.
N.M. Chau, A New Similarity Measure of Picture Fuzzy Sets and Application in the Fault Diagnosis of Steam Turbine, I. J. Mathematical Sciences and Computing, 5(2020), 47-55.
N.V. Dinh and N.X. Thao, Some measures of picture fuzzy sets and their application in multi-attribute decision making, Int. J. Math. Sci. Comput., 4(3) (2018), 23-41.
N.X. Thao, Similarity measures of picture fuzzy sets based on entropy and their application in MCDM, Pattern Analysis and Applications 11(2019), 1–11. https://doi.org/10.1007/s10044-019-00861-9
P. Dutta and S. Ganju, Some aspects of picture fuzzy set. Transactions of A. Razmadze Mathematical Institute 172(2018), 164–175.
P. Meksavang et. al., An extended picture fuzzy VIKOR approach for sustainable supplier management and its application in the beef industry. Symmetry 11(4) (2019), 468.
P. Singh, Correlation coefficients for picture fuzzy sets, J Intell Fuzzy Syst 27(2015), 2857–2868.
R. Kadian and S. Kumar, A new picture fuzzy divergence measure based on Jensen–Tsalli information measure and its application to multicriteria decision making, Granular Computing, (2021), https://doi.org/10.1007/s41066-021-00254-6.
R. Wang, Methods for MADM with picture fuzzy Muirhead mean operators and their application for evaluating the financial investment risk, Symmetry 11(6) (2019).
S. Dogra and M. Pal, Picture fuzzy matrix and its application. Soft Computing, (2020), https://doi.org/10.1007/s00500-020-05021-4.
Silambarasan, Some Algebraic Properties of Picture Fuzzy Sets, Bull. Int. Math. Virtual Inst. 11(3)(2021), 429-442.
S. Khan, S. Abdullah and S. Ashraf, Picture fuzzy aggregation information based on Einstein operations and their application in decision making, Mathematical Sciences 13(3) (2019), 213–229
S. Singh and A.H. Ganie, Applications of a picture fuzzy correlation coefficient in pattern analysis and decision-making, Granular Computing, (2021). https://doi.org/10.1007/s41066-021-00269 z(0123456789)
X. Peng and J. Dai, Algorithm for picture fuzzy multiple attribute decision making based on new distance measure, Int. J. Uncertain. Quant. 7(2017), 177–187.
X.T. Nguyen, Evaluating Water Reuse Applications under Uncertainty: A Novel Picture Fuzzy Multi Criteria Decision Making Medthod, International Journal of Information Engineering and Electronic Business 10(6)(2018), 32-39.
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