1. K. T. Atanassov, Intuitionistic fuzzy sets, Fuzzy sets and Systems, 20(1) (1986), 87–96.
2. S. Broumi, F. Smarandache and M. Dhar, Rough neutrosophic sets, Infinite Study, 2014.
3. S. Broumi, M. Talea, A. Bakali and F. Smarandache, Single valued neutrosophic graphs, Journal of New theory, 10 (2016), 86–101.
4. C. Cornelis, M. De Cock and E. E. Kerre, Intuitionistic fuzzy rough sets: at the crossroads of imperfect knowledge, Expert systems, 20(5) (2003), 260–270.
5. B. Davvaz, A short note on algebraic T-rough sets, Inform. Sci., 178(16) (2008), 3247– 3252.
6. I. Deli and S. Broumi, Neutrosophic soft matrices and nsm-decision making, Journal of Intelligent & Fuzzy Systems, 28(5) (2015), 2233–2241.
7. A. Gomolinska and M. Wolski, Rough inclusion functions and similarity indices, Fund. Inform., 133(2) (2014), 149–163.
8. M. R. Hooshmandasl, A. Shakiba, A. K. Goharshady and A. Karimi, S-Approximation: A new approach to algebraic approximation, Journal of Discrete Mathematics, 2014(1) (2014), 1–5.
9. T. Y. Lin and Y. Y. Yao, Mining soft rules using rough sets and neighborhoods, In Symposium on Modeling, Analysis and Simulation, CESA, 96 (1996), 1095–1100.
10. S. Luo and W. Xu, Rough Atanassov’s intuitionistic fuzzy sets model over two universes and its applications, The Scientific World Journal, 2014 (2014), Article ID: 348683.
11. Z. Pawlak, Rough sets, International Journal of Computer and Information Sciences, 11 (1982), 341–356.
12. L. Polkowski and A. Skowron, Rough mereology, In Zbigniew W. Ras and Maria Zemankova, editors, Methodologies for Intelligent Systems, Springer Berlin Heidelberg, 1994.
13. U. Rivieccio, Neutrosophic logics: Prospects and problems, Fuzzy sets and systems,159(14) (2008), 1860–1868.
14. G. Shafer, A mathematical theory of evidence, volume 1, Princeton university press Princeton, 1976.
15. A. Shakiba, S-Approximation Spaces, in: Algebraic Methods in General Rough Sets, Cham: Springer International Publishing, (2019), 697–725.
16. A. Shakiba, Distributed decision making with S-approximation spaces, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 29(02) (2021), 281– 311.
17. A. Shakiba and M. R. Hooshmandasl, S-approximation spaces: A three-way decision approach, Fund. Inform., 139(3) (2015), 307–328.
18. A. Shakiba and M. R. Hooshmandasl, Neighborhood system S-approximation spaces and applications, Knowledge and Information Systems, 49(2) (2015) 1–46.
19. A. Shakiba, M. R. Hooshmandasl, B. Davvaz and S. A. Shahzadeh Fazeli, An intuitionistic fuzzy approach to S-approximation spaces, Journal of Intelligent & Fuzzy Systems, 30(6) (2016), 3385–3397.
20. A. Shakiba, M. R. Hooshmandasl, B. Davvaz and S. A. Shahzadeh Fazeli, SApproximation spaces: A fuzzy approach, Iran. J. Fuzzy Syst., 14(2) (2017), 127–154.
21. A. Shakiba, A. Kafshdar Goharshady, M. R. Hooshmandasl and M. A. Meybodi, A note on belief structures and S-approximation spaces, Iran. J. Math. Sci. Inform., 15(2) (2020), 117–128.
22. F. Smarandache, Neutrosophy: neutrosophic probability, set, and logic: analytic synthesis & synthetic analysis, 1998.
23. F. Smarandache et al., A unifying field in logics. neutrosophy: Neutrosophic probability, set and logic, 1999.
24. B. Sun and W. Ma, Fuzzy rough set model on two different universes and its application, Appl. Math. Model., 35(4) (2011), 1798–1809.
25. C. A. C. Sweety and I. Arockiarani, Rough sets in neutrosophic approximation space, Ann. Fuzzy Math. Inform., 13(4) (2017), 449–463.
26. H. Wang, F. Smarandache, Y. Zhang and R. Sunderraman, Single valued neutrosophic sets, Multispace and Multistruct, 4 (2010), 410–413.
27. H. Wu, Y. Yuan, L. Wei and L. Pei, On entropy, similarity measure and cross-entropy of single-valued neutrosophic sets and their application in multi-attribute decision making, Soft Computing, 22(22) (2018), 7367–7376.
28. H. L. Yang, Z. L. Guo, Y. She and X. Liao, On single valued neutrosophic relations, Journal of Intelligent & Fuzzy Systems, 30(2) (2016), 1045–1056.
29. H. L. Yanga, Y. L. Baoa, and Z. L. Guob, Generalized interval neutrosophic rough sets and its application in multi-attribute decision making, Filomat, 32(1) (2018), 11–33.
30. Y. Yao, An outline of a theory of three-way decisions, In International conference on rough sets and current trends in computing, Berlin, Heidelberg: Springer Berlin Heidelberg, (2012), 1–17.
31. Y. Y. Yao, Relational interpretations of neighborhood operators and rough set approximation operators, Inform. Sci., 111(1–4) (1998), 239–259.
32. J. Ye, Single-valued neutrosophic minimum spanning tree and its clustering method, Journal of intelligent Systems, 23(3) (2014), 311–324.
33. C. Zhang, D. Li, Xiangping Kang, D. Song, A. K. Sangaiah and S. Broumi, Neutrosophic fusion of rough set theory: An overview, Computers in Industry, 115 (2020), Article ID: 103117
)