Foundations and framework of superhypersoft sets
Foundations and framework of superhypersoft sets
Resumo
Superhypersoft sets (SHSS) represent an advanced extension of soft sets and hypersoft sets,
designed to address complex multi-parameterized decision-making problems in uncertain environments. This
study explores the foundational theories of soft set and hypersoft set models, leading to the formulation of
SHSS as a more generalized and flexible framework for managing intricate data structures. We define key
operations and properties of SHSS and establish their basic algebraic laws. The findings show that SHSS
improves the mathematical abilities of existing soft set models by adding more structural complexity, which
makes them suitable for complicated classification and decision-support systems. Even with such potential,
SHSS is still a relatively new field with many undiscovered research possibilities, such as formalization of
basic operations, discussion of basic algebraic laws, algorithmic implementations and real-world applications
in different fields. This study inspires more developments in soft set theory and uncertainty modeling by
establishing the foundation for future research into the theoretical and applied aspects of SHSS.
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Referências
https://doi.org/10.1016/S0898-1221(99)00056-5
2. F. Smarandache, A unifying field in logics: Neutrosophic logic, American Research Press, 2005.
3. F. Karaaslan, Neutrosophic Soft Sets with Applications in Decision Making, International Journal of Information Science
and Intelligent System, 4(2), (2015), 1-20. http://dx.doi.org/10.5281/zenodo.23151
4. H. J. Zimmermann, Fuzzy set theory, Wiley interdisciplinary reviews: computational statistics, 2(3), (2010), 317-332.
https://doi.org/10.1002/wics.82
5. J. Maiers and Y.S. Sherif, Applications of fuzzy set theory, IEEE Transactions on Systems, Man and Cybernetics, 15(1),
(1985), 175-189. https://doi.org/10.1109/TSMC.1985.6313408
6. K. T. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20(1), (1986), 87–96. https://doi.org/10.1016/S0165-
0114(86)80034-3
7. L. A. Zadeh, Fuzzy sets, Information and Control, 8(3), (1965), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-
X
8. M. Saeed, M. Ahsan, M.K. Siddique and M.R. Ahmad, A study of the fundamentals of hypersoft set theory, International
Journal of Scientific and Engineering Research, 11(1),(2020) 230.
9. P. K. Maji, R. Biswas and A. R. Roy, Soft set theory, Computers & Mathematics with Applications, 45(4-5), (2003),
555–562. https://doi.org/10.1016/S0898-1221(03)00016-6
10. P. K. Maji, Neutrosophic soft set, Annals of Fuzzy Mathematics and Informatics, 5(1), (2013), 157–168.
11. T. Fujita and F. Smarandache, An Introduction to Advanced Soft Set Variants: SuperHyperSoft Sets, IndetermSuper-
HyperSoft Sets, IndetermTreeSoft Sets, BiHyperSoft sets, GraphicSoft sets and Beyond, Neutrosophic Sets and Systems,
82,(2025), 817-843.
12. Z. Pawlak, Rough sets, International Journal of Computer & Information Sciences, 11(5),(1982) 341–356.
https://doi.org/10.1007/BF01001956
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