Fermatean Fuzzy Maximal Subgroup and its Characterizations
Authors
A.Sheela Roselin
Research scholar, Reg.No.22123272092005, Department of Mathematics, Vivekananda college, Agasteeswaram, Kanyakumari-629 701, Tamilnadu (IN)
D.Jayalakshmi
Associate Professor, Department of Mathematics, Vivekananda College, Agasteeswaram, Kanyakumari-629 701, Tamilnadu (IN)
G.Subbiah*
Associate Professor, Department of Mathematics, Sri K.G.S Arts College, Srivaikuntam-628 619, Tamilnadu (IN)
Article Information
DOI: 10.51583/IJLTEMAS.2026.15020000037
Subject Category: Mathematics
Volume/Issue: 15/2 | Page No: 412-422
Publication Timeline
Submitted: 2026-03-06
Published: 2026-03-05
Abstract
In this article, we investigate the concept of fermatean fuzzy characteristic subgroup of a group and fermatean fuzzy normal subgroup. The level subset of fermatean fuzzy subgroup and its properties also defined. Finally, the homomorphic image of fermatean fuzzy subgroup is also discussed.
Keywords
fuzzy set, fermatean fuzzy set, subgroup, characteristic, level subset, homomorphism
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References
1. Ahn. T. C, Hur. K, Jang. K. W & Roh. S. B (2006), Intuitionistic fuzzy subgroups, [Google Scholar] [Crossref]
2. Honam Mathematical Journal, 28(1), 31–44. [Google Scholar] [Crossref]
3. Ahn. T. C, Jang. K. W, Roh. S. B & Hur. K (2005), A note on intuitionistic fuzzy [Google Scholar] [Crossref]
4. subgroups, Proceedings of KFIS Autumn Conference 2005, 15(2), 496–499. [Google Scholar] [Crossref]
5. Anthony. J. M & Sherwood. H (1982), A characterization of fuzzy subgroups, Fuzzy Sets and Systems, 7(3), 297–305. [Google Scholar] [Crossref]
6. Atanassov. K. T (1983), Intuitionistic fuzzy sets, VII ITKR’s Session, Sofia, June 1983 [Google Scholar] [Crossref]
7. (Deposed in Central Science-Technical Library of Bulgaria Academic of Science, 1697/84) [Google Scholar] [Crossref]
8. (in Bulgarian). Reprinted: International Journal Bioautomation, 2016, 20(S1), S1–S6. [Google Scholar] [Crossref]
9. Atanassov. K. T (1986), Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20(1), 87–96. [Google Scholar] [Crossref]
10. Atanassov. K. T (1994), New operations defined over the intuitionistic fuzzy sets, Fuzzy [Google Scholar] [Crossref]
11. Sets and Systems, 61(2), 137–142. [Google Scholar] [Crossref]
12. Bal. M, Ahmad. K.D, Hajjari. A.A & Ali. R (2022), A short note on the kernel subgroup of intuitionistic fuzzy groups, Journal of Neutrosophic and Fuzzy Systems, 2(1), 14–20. [Google Scholar] [Crossref]
13. Biswas. R (1989), Intuitionistic fuzzy subgroups, Mathematical Forum, 10, 37–46. [Google Scholar] [Crossref]
14. Biswas. R (1997), Intuitionistic fuzzy subgroups, Notes on Intuitionistic Fuzzy Sets, 3(2), [Google Scholar] [Crossref]
15. 53–60. [Google Scholar] [Crossref]
16. B. C. Cuong, Picture fuzzy sets-first results part 2, Seminar Neuro-Fuzzy Systems with Applications, Preprint 04/2013, Institute of Mathematics, Journal of Computer Science and Cybernetics, 30(4)(2014), 409–420. [Google Scholar] [Crossref]
17. Ejegwa. P. A, Ajogwu. C. F & Sarkar. A (2023), A hybridized correlation coefficient [Google Scholar] [Crossref]
18. technique and its application in classification process under intuitionistic fuzzy setting, [Google Scholar] [Crossref]
19. Iranian Journal of Fuzzy Systems, 20(4), 103–120. [Google Scholar] [Crossref]
20. Fathi. M & Salleh. A. R (2009), Intuitionistic fuzzy groups, Asian Journal of Algebra, [Google Scholar] [Crossref]
21. 2(1), 1–10. [Google Scholar] [Crossref]
22. Hadi. I.M, On some special fuzzy ideal of fuzzy ring, Accepted in J. Soc. of [Google Scholar] [Crossref]
23. Phy-Math(2000). [Google Scholar] [Crossref]
24. Hamil. M.A, Semi prime fuzzy modules, Ibn. Al-Haitham J. pure and applied science, 25(1) (2012), 1-10. [Google Scholar] [Crossref]
25. H. Z. Ibrahim, T. M. Al-shami and O. G. Elbarbary, (3, 2)-fuzzy sets and their applications to topology and optimal choice, Computational Intelligence and Neuroscience, 2021 (2021), 14 pages. [Google Scholar] [Crossref]
26. Nagotia. X.V and Ralescu.D, Application of fuzzy sets and system analysis, Birkhauser, Basel, 1975. [Google Scholar] [Crossref]
27. Rosenfeld. A (1971), Fuzzy groups, Journal of Mathematical Analysis and Applications, [Google Scholar] [Crossref]
28. 35(3), 512–517. [Google Scholar] [Crossref]
29. T. Senapati and R.R. Yager, Fermatean fuzzy sets, Journal of Ambient Intelligence and Humanized computing, 11, (2) (2020), 663-674. [Google Scholar] [Crossref]
30. F. Smarandache (2003), Definition of Neutrosophic Logic – A Generalization of the Intuitionistic Fuzzy Logic, Proceedings of the Third Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2003, September 10-12, 2003, Zittau, Germany; University of Applied Sciences at Zittau/Goerlitz, 141-146. [Google Scholar] [Crossref]
31. Xu. C (2008), New structures of intuitionistic fuzzy groups, In: Huang. D. S, Wunsch. [Google Scholar] [Crossref]
32. D. C, Levine D. S, & Jo. K. H (eds), Advanced Intelligent Computing Theories and Applications, With Aspects of Contemporary Intelligent Computing Techniques. Communications in Computer and Information Science, vol 15. Springer, Berlin,Heidelberg, 145–152. [Google Scholar] [Crossref]
33. Yuan. X. H, Li. H. X and Lee. E. S (2010), On the definition of the intuitionistic fuzzy [Google Scholar] [Crossref]
34. Subgroups, Computers and Mathematics with Applications, 59(9), 3117–3129. [Google Scholar] [Crossref]
35. R.R.Yager, Pythagorean fuzzy subsets, In:2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 2013, 36286152. [Google Scholar] [Crossref]
36. Zadeh. L. A (1965), Fuzzy sets, Information and Control, 8(3), 338–353. [Google Scholar] [Crossref]
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