Volume 24 , Issue 2 , PP: 147-162, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
V. Vijayalakshmi 1 , S. Sahaya Jude Dhas 2 , T. T. Raman 3 , Aiyared Iampan 4 *
Doi: https://doi.org/10.54216/IJNS.240213
We introduce the concept of sine trigonometric (g1, g2, g3) neutrosophic normal interval valued set. An identifying sine trigonometric (g1, g2, g3)neutrosophic normal interval valued set is a combination of (g1, g2, g3) neutrosophic interval valued set and neutrosophic interval valued set. We communicate the new aggregating operator such as sine trigonometric (g1, g2, g3) neutrosophic normal interval valued weighted averaging, sine trigonometric (g1, g2, g3) neutrosophic normal interval valued weighted geometric, sine trigonometric generalized (g1, g2, g3) neutrosophic normal interval valued weighted averaging and sine trigonometric generalized (g1, g2, g3) neutrosophic normal interval valued weighted geometric.
Aggregating operator , weighted averaging , weighted geometric , generalized weighted averaging and generalized weighted geometric.
[1] L. A. Zadeh, Fuzzy sets, Information and control, 8(3), (1965), 338-353.
[2] I.B. Turksen, Interval valued fuzzy sets based on normal forms, Fuzzy Sets and Systems, 20, (1986), 191-210.
[3] R. R. Yager, Pythagorean membership grades in multi criteria decision-making, IEEE Trans. Fuzzy Systems, 22, (2014), 958-965.
[4] X. Peng, and Y. Yang, Fundamental properties of interval valued pythagorean fuzzy aggregation operators, International Journal of Intelligent Systems, (2015), 1-44.
[5] F. Smarandache, A unifying field in logics, Neutrosophy neutrosophic probability, set and logic, American Research Press, Rehoboth, (1999).
[6] H.Wang, F. Smarandache, Y. Q. Zhang and R. Sunderraman, Interval neutrosophic sets and logic, Theory and applications in computing, (2005), 6-14.
[7] R.N. Xu and C.L. Li, Regression prediction for fuzzy time series, Appl. Math. J. Chinese Univ., 16, (2001), 451-461.
[8] K. Atanassov, Intuitionistic fuzzy sets, Fuzzy sets and Systems, 20(1), (1986), 87-96.
[9] M. Akram, W. A. Dudek, Farwa Ilyas, Group decision making based on Pythagorean fuzzy TOPSIS method, Int. J. Intelligent System, 34(2019), 1455-1475.
[10] M. Akram, W. A. Dudek, J. M. Dar, Pythagorean Dombi Fuzzy Aggregation Operators with Application in Multi-criteria Decision-making, Int. J. Intelligent Systems, 34,(2019), 3000-3019.
[11] M. Akram, X. Peng, A. N. Al-Kenani, A. Sattar, Prioritized weighted aggregation operators under complex Pythagorean fuzzy information, Journal of Intelligent and Fuzzy Systems, 39(3), (2020), 4763-4783.
[12] K. Rahman, S. Abdullah,, M. Shakeel, MSA. Khan and M. Ullah, Interval valued Pythagorean fuzzy geometric aggregation operators and their application to group decision-making problem, Cogent Mathematics, 4, (2017), 1-19.
[13] M.S.A. Khan, The Pythagorean fuzzy Einstein Choquet integral operators and their application in group decision making, Comp. Appl. Math. 38, 128, (2019), 1-35.
[14] K. Rahman, A. Ali, S. Abdullah and F. Amin, Approaches to multi attribute group decision-making based on induced interval valued Pythagorean fuzzy Einstein aggregation operator, New Mathematics and Natural Computation, 14(3), (2018), 343-361.
[15] M Palanikumar, K Arulmozhi, MCGDM based on TOPSIS and VIKOR using Pythagorean neutrosophic soft with aggregation operators, Neutrosophic Sets and Systems,, 538-555, 2022.
[16] 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.
[17] Iampan, A, Spherical Fermatean interval valued fuzzy soft set based on multi criteria group decision making, International Journal of Innovative Computing, Information and Control 2022, 18(2), 607–619.
[18] Iampan, A, Novel approach to decision making based on type-II generalized Fermatean bipolar fuzzy soft sets, International Journal of Innovative Computing, Information and Control 2022, 18(3), 769–781.
[19] Palanikumar, M., Arulmozhi, K, On intuitionistic fuzzy normal subbisemiring of bisemiring, Nonlinear Studies 2021, 28(3), 717–721.
[20] Z. Yang, J. Chang, Interval-valued Pythagorean normal fuzzy information aggregation operators for multiple attribute decision making approach, IEEE Access, 8, (2020), 51295-51314.
[21] R. Jansi, K. Mohana and F. Smarandache, Correlation Measure for Pythagorean Neutrosophic Sets with T and F as Dependent Neutrosophic Components Neutrosophic Sets and Systems,30, (2019), 202-212.
[22] G. Shahzadi, M. Akram and A. B. Saeid, An application of single-valued neutrosophic sets in medical diagnosis, Neutrosophic Sets and Systems, 18, (2017), 80-88.
[23] P.K. Singh, Single-valued neutrosophic context analysis at distinct multi-granulation. Comp. Appl. Math. 38, 80 (2019), 1-18.
[24] P.A. Ejegwa, Distance and similarity measures for Pythagorean fuzzy sets, Granular Computing, (2018), 1-17.
[25] T.M. Al. shami, (2,1)-Fuzzy sets: properties, weighted aggregated operators and their applications to multi-criteria decision-making methods, Complex & Intelligent Systems, (2022), 1-19.
[26] T. M. Al. shami and A. Mhemdi, Generalized frame for orthopair fuzzy sets, (m, n)-fuzzy sets and their applications to multi-criteria decision-making methods, information, 14(56), (2023), 1-21.
[27] M.S Yang, C.H. Ko, On a class of fuzzy c-numbers clustering procedures for fuzzy data, Fuzzy Sets and Systems, 84, (1996), 49-60.
[28] 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 Computing, 1-27, 2023.
[29] 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), 1129–1138, 2022.
[30] M Palanikumar, K Arulmozhi, C. Jana, Multiple attribute decision-making approach for Pythagorean neutrosophic normal interval-valued fuzzy aggregation operators, Comput. Appl. Math., 41(90), (2022), 1-22.