Volume 25 , Issue 4 , PP: 203-217, 2025 | Cite this article as | XML | Html | PDF | Full Length Article
Aiyared Iampan 1 * , Murugan Palanikumar 2 , T. T. Raman 3
Doi: https://doi.org/10.54216/IJNS.250417
A novel technique to produce complicated tangent trigonometric (ζ,∂,e) neutrosophic sets is presented in this study. Complex tangent trigonometric (ζ,∂,e) neutrosophic weighted averaging, geometric, generalized weighted averaging, and generalized weighted geometric will all be discussed in this article. We calculated the weighted average and geometric using an aggregating model. The following algebraic methods will be used to further study several sets having significant properties.
A novel technique to produce complicated tangent trigonometric (&zeta , ,&part , ,e) neutrosophic sets is presented in this study. Complex tangent trigonometric (&zeta , ,&part , ,e) neutrosophic weighted averaging, geometric, generalized weighted averaging, and generalized weighted geometric will all be discussed in this article. We calculated the weighted average and geometric using an aggregating model. The following algebraic methods will be used to further study several sets having significant properties.
[1] L. A. Zadeh, Fuzzy sets, Information and control, 8(3), (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] Wang, P., Zhu, B., Yu, Y., Ali, Z., & Almohsen, B. Complex intuitionistic fuzzy DOMBI prioritized aggregation operators and their application for resilient green supplier selection. Facta Universitatis, Series: Mechanical Engineering, 21(3), (2023), 339-357.
[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 Communication Technologies (WICT 2013), IEEE, (2013), 1–6.
[6] 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.
[7] Hussain, A., & Ullah, K. An Intelligent Decision Support System for Spherical Fuzzy Sugeno-Weber Aggregation Operators and Real-Life Applications. Spectrum of Mechanical Engineering and Operational Research, 1(1), (2024), 177-188.
[8] M. Rafiq, S. Ashraf, S. Abdullah, T. Mahmood, S. Muhammad, The cosine similarity measures of spherical fuzzy sets and their applications in decision making. Journal of Intelligent & Fuzzy Systems, 36(6), 2019, 6059-6073.
[9] T. Senapati, R.R. Yager, Fermatean, fuzzy sets. J. Ambient Intell. Humaniz. Comput. 11, (2020), 663- 674.
[10] R.R. Yager, Generalized Orthopair Fuzzy Sets. IEEE Trans Fuzzy Syst 25(5), 2016, 1222-1230.
[11] MPalanikumar, K Arulmozhi, C Jana, Multiple attribute decision-making approach for Pythagorean neutrosophic normal interval-valued fuzzy aggregation operators, Computational and Applied Mathematics, 41(3), (2022)
[12] Z. Xu, R.R. Yager, Some geometric aggregation operators based on intuitionistic fuzzy sets, Int. J. Gen. Syst. 35, (2006), 417–433.
[13] D.F. Li, Multi-attribute decision making method based on generalized OWA operators with intuitionistic fuzzy sets, Expert Syst. Appl. 37, (2010), 8673–8678.
[14] S. Zeng, W. Sua, Intuitionistic fuzzy ordered weighted distance operator, Knowl. Based Syst. 24, (2011), 1224–1232.
[15] X. Peng, H. Yuan, Fundamental properties of Pythagorean fuzzy aggregation operators, Fundam. Inform. 147, (2016), 415–446.
[16] S. Ashraf, S. Abdullah, T. Mahmood, Spherical fuzzy Dombi aggregation operators and their application in group decision making problems, J. Amb. Intell. Hum. Comput. 11, (2020), 2731–2749.
[17] K. Ullah, H. Garg, T. Mahmood, N. Jan, Z. Ali, Correlation coefficients for T-spherical fuzzy sets and their applications in clustering and multi-attribute decision making, Soft Comput. 24, (2020), 1647–1659.
[18] K. Ullah, T. Mahmood, H. Garg, Evaluation of the performance of search and rescue robots using Tspherical fuzzy hamacher aggregation operators, Int. J. Fuzzy Syst. 22, (2020), 570–582.
[19] Abu, Ibraheem. , Al-Husban, Abdallah. , J., Lejo. , J., Jamil. , Palanikumar, M., Balaji, G..(2024) Selectionprocess real-life application for new type complex neutrosophic sets using various aggregation operators. International Journal of Neutrosophic Science, 23(4) 136 153.
[20] J., Lejo. , Damrah, Sadeq. , M., Mutaz. , Al-Husban, Abdallah. , Palanikumar, M.. (2024). Type-I extension Diophantine neutrosophic interval valued soft set in real life applications for a decision making. International Journal of Neutrosophic Science, 24(4), 151-164.
[21] M. Palanikumar, K. Arulmozhi, A Iampan, Multi criteria group decision making based on VIKORand TOPSIS methods for Fermatean fuzzy soft with aggregation operators, ICIC Express Letters 16 (10), (2022), 1129–1138.
[22] M. Palanikumar, K. Arulmozhi, MCGDM based on TOPSIS and VIKORusing Pythagorean neutrosophic soft with aggregation operators, Neutrosophic Sets and Systems, (2022), 538–555.
[23] 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.