Convexity cum concavity on refined fuzzy set with some properties

Authors

  • Muhammad Arshad Department of Mathematics, University of Management and Technology, Lahore 54000, Pakistan.
  • Muhammad Saeed Department of Mathematics, University of Management and Technology, Lahore 54000, Pakistan.
  • Atiqe Ur Rahman * Department of Mathematics, University of Management and Technology, Lahore 54000, Pakistan. https://orcid.org/0000-0001-6320-9221

https://doi.org/10.48313/uda.v1i1.34

Abstract

Smarandache refined fuzzy sets to handle an object's sub-membership degrees. Applications for fuzzy convexity are numerous and include pattern recognition, optimization, and related issues. By taking into account a more precise definition of fuzzy sets, these applications can be handled more effectively. This paper uses theoretical and analytical techniques to construct the novel idea of convexity cum concavity on refined fuzzy sets. The convex (concave) fuzzy sets proposed by Zadeh [1], [2] and Chaudhuri [3], [4] are extended in this work. Some of its significant findings are also generalizable.

Keywords:

Refined fuzzy set‎, Concave refined fuzzy set, Convex refined fuzzy set, Ortho-concave refined fuzzy set, Ortho-convex refined fuzzy set

References

  1. [1] Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X

  2. [2] Zadeh, L. A. (1999). Fuzzy sets as a basis for a theory of possibility. Fuzzy sets and systems, 100, 9–34. https://doi.org/10.1016/S0165-0114(99)80004-9

  3. [3] Chaudhuri, B. B. (1992). Concave fuzzy set: A concept complementary to the convex fuzzy set. Pattern recognition letters, 13(2), 103–106. https://doi.org/10.1016/0167-8655(92)90040-7

  4. [4] Chaudhuri, B. B. (1991). Some shape definitions in fuzzy geometry of space. Pattern recognition letters, 12(9), 531–535. https://doi.org/10.1016/0167-8655(91)90113-Z

  5. [5] Dubois, D., & Prade, H. (1983). Ranking fuzzy numbers in the setting of possibility theory. Information sciences, 30(3), 183–224. https://doi.org/10.1016/0020-0255(83)90025-7

  6. [6] Liang, L. R., Lu, S., Wang, X., Lu, Y., Mandal, V., Patacsil, D., & Kumar, D. (2006). FM-test: A fuzzy-set-theory-based approach to differential gene expression data analysis. BMC bioinformatics, 7, 1–13. https://doi.org/10.1186/1471-2105-7-S4-S7

  7. [7] Beg, I., & Ashraf, S. (2009). Similarity measures for fuzzy sets. Appied computer mathematic, 8(2), 192–202. https://www.researchgate.net/profile/Ismat-Beg/publication/228744370_Similarity_measures_for_fuzzy_sets/links/5835651208aef19cb8224581/Similarity-measures-for-fuzzy-sets

  8. [8] Vemuri, N. R., Hareesh, A. S., & Srinath, M. S. (2014). Set difference and symmetric difference of fuzzy sets. https://www.math.sk/fsta2014/presentations/VemuriHareeshSrinath

  9. [9] Neog, T. J., & Sut, D. K. (2011). Complement of an extended fuzzy set. International journal of computer, 29(3), 39-45. https://www.academia.edu/download/80142177/pxc3874852.pdf

  10. [10] Yager, R. R. (2013). Pythagorean membership grades in multicriteria decision making. IEEE transactions on fuzzy systems, 22(4), 958–965. https://doi.org/10.1109/TFUZZ.2013.2278989

  11. [11] Biswas, R. (1995). An application of fuzzy sets in students’ evaluation. Fuzzy sets and systems, 74(2), 187–194. https://doi.org/10.1016/0165-0114(95)00063-Q

  12. [12] McBratney, A. B., & Odeh, I. O. A. (1997). Application of fuzzy sets in soil science: fuzzy logic, fuzzy measurements and fuzzy decisions. Geoderma, 77(2–4), 85–113. https://doi.org/10.1016/S0016-7061(97)00017-7

  13. [13] Mamdani, E. H. (1974). Application of fuzzy algorithms for control of simple dynamic plant. In Proceedings of the institution of electrical engineers (Vol. 121, No. 12, pp. 1585-1588). IEE. https://doi.org/10.1049/piee.1974.0328

  14. [14] Syau, Y. R. (1999). On convex and concave fuzzy mappings. Fuzzy sets and systems, 103(1), 163–168. https://doi.org/10.1016/S0165-0114(97)00210-8

  15. [15] Sarkar, D. (1996). Concavoconvex fuzzy set. Fuzzy sets and systems, 79(2), 267–269. https://doi.org/10.1016/0165-0114(95)00089-5

  16. [16] Tahayori, H., Tettamanzi, A. G. B., Degli Antoni, G., Visconti, A., & Moharrer, M. (2010). Concave type-2 fuzzy sets: Properties and operations. Soft computing, 14, 749–756. https://doi.org/10.1007/s00500-009-0462-9

  17. [17] Weber, S. (1984). Measures of fuzzy sets and measures of fuzziness. Fuzzy sets and systems, 13(3), 247–271. https://doi.org/10.1016/0165-0114(84)90060-5

  18. [18] Pal, N. R., & Bezdek, J. C. (1994). Measuring fuzzy uncertainty. IEEE transactions on fuzzy systems, 2(2), 107–118. https://doi.org/10.1109/91.277960

  19. [19] Smarandache, F. (2019). Neutrosophic set is a generalization of intuitionistic fuzzy set, inconsistent intuitionistic fuzzy set (picture fuzzy set, ternary fuzzy set), Pythagorean fuzzy set, spherical fuzzy set, and q-rung orthopair fuzzy set, while neutrosophication is a genera. Journal of new theory, (29), 1–31. https://dergipark.org.tr/en/pub/jnt/issue/51172/666629

Published

2024-06-29

How to Cite

Arshad, M. ., Saeed, M. ., & Ur Rahman, A. . (2024). Convexity cum concavity on refined fuzzy set with some properties. Uncertainty Discourse and Applications, 1(1), 140-150. https://doi.org/10.48313/uda.v1i1.34

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