Volume 25 , Issue 2 , PP: 233-253, 2025 | Cite this article as | XML | Html | PDF | Full Length Article
R. Balaji 1 , Murugan Palanikumar 2 , Aiyared Iampan 3 *
Doi: https://doi.org/10.54216/IJNS.250220
The notion of the complex Q bipolar neutrosophic subbisemiring (CQBNSBS) is a fundamental notion to be considered for tackling tricky and intricate information. Here, in this study, we want to expand the notion of CQBNSBS by giving a general algebraic structure for tackling bipolar complex fuzzy (BCF) data by fusing the conception of CQBNSBS and subbisemiring. Keeping in view the importance of fuzzy algebraic structures, in this manuscript, we develop the concept of CQBNSBS. We analyze the important properties and homomorphic aspects of CQBNSBS. For bisemirings, we propose the CQBNSBS level sets. We also develop the notions of homomorphic images of all CQBNSBSs is also CQBNSBS and homomorphic pre-images of all CQBNSBSs is also CQBNSBS. Examples are provided to demonstrate our findings.
CQBNSBS , SBS , Homomorphism
[1] L. A. Zadeh, Fuzzy sets, Information and Control, 8, (1965), 338-353.
[2] K. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20(1), (1986) 87-96.
[3] R. R. Yager, Pythagorean membership grades in multi criteria decision-making, IEEE Trans. Fuzzy Systems, 22, (2014), 958-965.
[4] S. Ashraf, S. Abdullah, T. Mahmood, F. Ghani and T. Mahmood, Spherical fuzzy sets and their applications in multi-attribute decision making problems, Journal of Intelligent and Fuzzy Systems, 36, (2019), 2829-284.
[5] B.C. Cuong and V. Kreinovich, Picture fuzzy sets a new concept for computational intelligence problems, in Proceedings of 2013 Third World Congress on Information and Cmunication Technologies (WICT 2013), IEEE, (2013), 1-6.
[6] W. R. Zhang, Bipolar fuzzy sets and relations: a computational framework for cognitive modeling and multiagent decision analysis, In Proceedings of the first international joint conference of the north american fuzzy information processing society biannual conference, the industrial fuzzy control and intellige, IEEE, (1994), 305-309.
[7] K. M. Lee,Comparasion of interval valued fuzzy sets, intuitionistic fuzzy sets, and bipolar fuzzy sets. J. Fuzzy Logic Intel Syst. 14 (2004), 125-129
[8] F. Smarandache, A unifying field in logics Neutrosophy Neutrosophic Probability, Set and Logic, Rehoboth American Research Press (1999).
[9] Daniel Ramot, Ron Milo, Menahem Friedman, and Abraham Kandel, complex fuzzy set, IEEE Transactions on Fuzzy System, 10(2), 2002.
[10] S.J Golan, Semirings and their Applications, Kluwer Academic Publishers, London, 1999.
[11] Faward Hussian, Raja Muhammad Hashism, Ajab Khan, Muhammad Naeem, Generalization of bisemirings, International Journal of Cputer Science and Information Security, 14(9), (2016), 275-289.
[12] J. Ahsan, K. Saifullah, and F. Khan, Fuzzy semirings, Fuzzy Sets and systems, 60, (1993), 309-320.
[13] M.K Sen, S. Ghosh An introduction to bisemirings, Southeast Asian Bulletin of Mathematics, 28(3) (2001), 547-559.
[14] Hasan, Z. ”Deep Learning for Super Resolution and Applications,” Journal of Galoitica: Journal of Mathematical Structures and Applications, vol. 8, no. 2, pp. 34-42, 2023.
[15] Roopadevi1,, P. Karpagadevi, M. Krishnaprakash, S. Broumi, S. Gomathi, S. ”Comprehensive Decision- Making with Spherical Fermatean Neutrosophic Sets in Structural Engineering,” Journal of International Journal of Neutrosophic Science, vol. 24, no. 4, pp. 432-450, 2024.
[16] SG Quek, H Garg, G Selvachandran,MPalanikumar, K Arulmozhi,VIKOR and TOPSIS framework with a truthful-distance measure for the (t, s)-regulated interval-valued neutrosophic soft set, Soft Cputing, 1–27, 2023.
[17] M Palanikumar, K Arulmozhi, A Iampan, Multi criteria group decision making based on VIKOR and TOPSIS methods for Fermatean fuzzy soft with aggregation operators, ICIC Express Letters 16 (10), (2022), 1129–1138.
[18] Mahmoud, H. Abdelhafeez, A. ”Spherical Fuzzy Multi-Criteria Decision-Making Approach for Risk Assessment of Natech,” Journal of Neutrosophic and Information Fusion, vol. 2, no. 1, pp. 59-68, 2023.
[19] M Palanikumar, S Broumi, Square root (l1, l2)phantine neutrosophic normal interval-valued sets and their aggregated operators in application to multiple attribute decision making, International Journal o Neutrosophic Science, 4, (2022).
[20] Ozcek, M. ”A Review on the Structure of Fuzzy Regular Proper Mappings in Fuzzy Topological Spaces and Their Properties,” Journal of Pure Mathematics for Theoretical Computer Science, vol. 3, no. 2, pp.60-71, 2023.
[21] Ali, O. Mashhadani, S. Alhakam, I. M., S. ”A New Paradigm for Decision Making under Uncertainty in Signature Forensics Applications based on Neutrosophic Rule Engine,” Journal of International Journal of Neutrosophic Science, vol. 24, no. 2, pp. 268-282, 2024.
[22] M Palanikumar, N Kausar, H Garg, A Iampan, S Kadry, M Sharaf, Medical robotic engineering selection based on square root neutrosophic normal interval-valued sets and their aggregated operators, AIMS Mathematics, 8(8), (2023), 17402–17432.
[23] A. Al Quran, A. G. Ahmad, F. Al-Sharqi, A. Lutfi, Q-complex Neutrosophic Setˆa, International Journal of Neutrosophic Science, 20(2), (2023), 08–19.
[24] F. Al-Sharqi, M. U. Romdhini, A. Al-Quran, Group decision-making based on aggregation operator and score function of Q-neutrosophic soft matrix, Journal of Intelligent and Fuzzy Systems, 45, (2023), 305– 321.
[25] F. Al-Sharqi, Y. Al-Qudah and N. Alotaibi, Decision-making techniques based on similarity measures of possibility neutrosophic soft expert sets. Neutrosophic Sets and Systems, 55(1), (2023), 358–382.
[26] F. Al-Sharqi, A. G. Ahmad, A. Al Quran, Mapping on interval complex neutrosophic soft sets, International Journal of Neutrosophic Science, 19(4), (2022), 77–85.
[27] A. Al-Quran, F. Al-Sharqi, K. Ullah, M. U. Romdhini, M. Balti and M. Alomai, Bipolar fuzzy hypersoft set and its application in decision making, International Journal of Neutrosophic Science, 20(4), (2023), 65–77.
