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Some similarity measures of rough interval Pythagorean fuzzy sets

Document Type : Research Paper

Authors

1 Department of Mathematics, Bharathidasan University, Tamilnadu, India.

2 Annamalai University, Chidambaram-608002, India.

Abstract

In this paper, we expose cosine, jaccard and dice similarity measures and rough interval Pythagorean mean operator. Some of the important properties of the defined similarity measures have been established. Then the proposed methods are applied for solving multi attribute decision making problems. Finally, a numerical example is solved to show the feasibility, applicability and effectiveness of the proposed strategies.

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References
[1]       Atanassov, K. (2016). Intuitionistic fuzzy sets. International journal bioautomation, 20, 87-96.
[2]       Hussain, A., Mahmood, T., & Ali, M. I. (2019). Rough Pythagorean fuzzy ideals in semigroups. Computational and applied mathematics, 38(2), 67.
[3]       Dubois, D.,  & Prade. H. (1990). Rough fuzzy sets and fuzzy rough sets. Int.J.General Syst, 17, 191-209.
[4]       Ejegwa, P. A. (2020). New similarity measures for Pythagorean fuzzy sets with applications. International journal of fuzzy computation and modelling, 3(1), 75-94.
[5]       Kumar, T., Bajaj, R., & Ansari, M. D. (2020). On accuracy function and distance measures of interval-valued Pythagorean fuzzy sets with application to decision making. Scientia iranica, 27(4), 2127-2139.
[6]       Kumar, R., Edalatpanah, S. A., Jha, S., & Singh, R. (2019). A Pythagorean fuzzy approach to the transportation problem. Complex & intelligent systems, 5(2), 255-263.
[7]       Pawlak, Z. (1982). Rough sets. International journal of computer & information sciences, 11(5), 341-356.
[8]       Pawlak, Z. (2002). Rough sets and intelligent data analysis. Information sciences, 147(1-4), 1-12.
[9]       Peng, X., & Yang, Y. (2016). Fundamental properties of interval‐valued Pythagorean fuzzy aggregation operators. International journal of intelligent systems, 31(5), 444-487.
[10]   Peng, X., & Li, W. (2019). Algorithms for interval-valued pythagorean fuzzy sets in emergency decision making based on multiparametric similarity measures and WDBA. Ieee access, 7, 7419-7441.
[11]   Peng, X., & Garg, H. (2019). Multiparametric similarity measures on Pythagorean fuzzy sets with applications to pattern recognition. Applied intelligence, 49(12), 4058-4096.
[12]   Ullah, K., Mahmood, T., Ali, Z., & Jan, N. (2020). On some distance measures of complex Pythagorean fuzzy sets and their applications in pattern recognition. Complex & intelligent systems, 6(1), 15-27.
[13]   Yager, R. R. (2013, June). Pythagorean fuzzy subsets. 2013 joint IFSA world congress and NAFIPS annual meeting (IFSA/NAFIPS) (pp. 57-61). IEEE.
[14]   Zadeh, L. A. (1975). The concept of a linguistic variable and it’s application to approximation reasoning I. Information sciences, 8,  199-249.
[15]   Zadeh, L. A. (1965).  Fuzzy sets.  Information control, 8 , 338-353.
Journal of Fuzzy Extension and Applications
Volume 1, Issue 4
December 2020
Pages 304-313
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