Applications of intuitionistic fuzzy sets to assessment, decision making and to topological spaces

  • Michael Gr. Voskoglou School of Engineering, University of Peloponnese, 26334 Patras, Greece
Ariticle ID: 325
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Keywords: fuzzy set, intuitionistic FS, soft set, fuzzy assessment, decision-making in fuzzy environment, intuitionistic fuzzy topological space

Abstract

The intuitionistic fuzzy sets, in which the elements of the universe have their membership and non-membership degrees in [0, 1], are a generalization of Zadeh’s fuzzy set. In this paper, intuitionistic fuzzy sets are used as tools for assessment and decision-making. This is useful in cases where one is not sure about the suitability of the linguistic characterizations assigned to each element of the universal set. Further, it is described how the notions of convergence, continuity, compactness, and of Hausdorff topological space are extended to intuitionistic fuzzy topological spaces. Applications illustrating our results are also presented.

References

Voskoglou M. Methods for Assessing Human–Machine Performance under Fuzzy Conditions. Mathematics. 2019, 7(3): 230. doi: 10.3390/math7030230

Berger JO. Statistical Decision Theory. Springer New York; 1980. doi: 10.1007/978-1-4757-1727-3

Zadeh LA. Fuzzy sets. Information and Control. 1965, 8(3): 338-353. doi: 10.1016/s0019-9958(65)90241-x

Bellman RE, Zadeh LA. Decision-Making in a Fuzzy Environment. Management Science. 1970, 17(4): B-141-B-164. doi: 10.1287/mnsc.17.4.b141

Alcantud JCR. Fuzzy Techniques for Decision Making. Symmetry 2018; 10(1): 6. doi: 10.3390/sym10010006

Zhu B, Ren P. Type-2 fuzzy numbers made simple in decision making. Fuzzy Optimization and Decision Making. 2021, 21(2): 175-195. doi: 10.1007/s10700-021-09363-y

Voskoglou MGr. An Application of Neutrosophic Sets to Decision Making. Neutrosophic Sets and Systems. 2023, 53: 1-9.

Atanassov KT. Intuitionistic fuzzy sets. Fuzzy Sets and Systems. 1986, 20(1): 87-96. doi: 10.1016/s0165-0114(86)80034-3

Ejegwa PA, Akubo AJ, Joshua OM. Intuitionistic Fuzzy Set and its Application in Career Determination via Normalized Euclidean Distance Method, European Scientific Journal. 2014, 10(15): 529-536.

Annamalai C. Intuitionistic Fuzzy Sets: New Approach and Applications. Available online: https://www.researchgate.net/publication/360395248 (accessed on 19 December 2023).

Atanassov KT. Intuitionistic Fuzzy Sets. Physica-Verlag HD, 1999. doi: 10.1007/978-3-7908-1870-3

Szmidt E, Kacprzyk J. Intuitionistic fuzzy sets in group decision making. Notes on Intuitionistic Fuzzy Sets. 1996, 2(1): 11–14.

Szmitd E, Kacprzyk J. Remarks on some applications of intuitionistic fuzzy sets in decision making. Notes on Intuitionistic Fuzzy Sets. 1996, 2(3): 22-31.

De SK, Biswas R, Roy AR. An application of intuitionistic fuzzy sets in medical diagnosis. Fuzzy Sets and Systems. 2001, 117(2): 209-213. doi: 10.1016/s0165-0114(98)00235-8

Szmitd E, Kacprzyk J. Intuitionistic fuzzy sets in same medical applications. Notes on Intuitionistic Fuzzy Sets. 2001, 7(4): 58–64.

Davvaz B, Hassani Sadrabadi E. An application of intuitionistic fuzzy sets in medicine. International Journal of Biomathematics. 2016, 9(3): 1650037. doi: 10.1142/s1793524516500376

Mohamed Kozae A, Shokry M, Omran M. Intuitionistic Fuzzy Set and Its Application in Corona Covid-19. Applied and Computational Mathematics. 2020, 9(5): 146. doi: 10.11648/j.acm.20200905.11

Atanassov K, Gargov G. Intuitionistic fuzzy logic. Comptes Rendus de L'Academie Bulgare des Sciences. 1990, 43(3): 9–12.

Atanassov K, Georgiev C. Intuitionistic fuzzy prolog. Fuzzy Sets and Systems. 1993, 53(2): 121-128. doi: 10.1016/0165-0114(93)90166-f

Meena K, Ponnappen L. An Application of Intuitionistic Fuzzy Sets in Choice of Discipline of Study. Global Journal of Pure and Applied Mathematics. 2018, 14(6): 867-871.

Molodtsov D. Soft set theory—First results. Computers & Mathematics with Applications. 1999, 37(4-5): 19-31. doi: 10.1016/s0898-1221(99)00056-5

Zadeh LA. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems. 1978, 1(1): 3-28. doi: 10.1016/0165-0114(78)90029-5

Klir GJ, Folger TA. Fuzzy sets, Uncertainty and Information. Prentice-Hall, London; 1988.

Voskoglou MGr. Generalizations of Fuzzy Sets and Related Theories. In: Voskoglou M (editor). An Essential Guide to Fuzzy Systems. Nova Science Publishers, NY; 2019. pp. 345-352.

Atanassov KT. 25 years of Intuitionistic Fuzzy Sets or: The most important mistakes and results of mine. In: Proceedings of the 7th International Workshop on Intuitionistic Fuzzy Sets and Generalizations, Warsaw, Poland, 2008.

Atanassova V. Intuitionistic Fuzzy Sets and Applications, Special Issue, Mathematics. Available online: https://www.mdpi.com/journal/mathematics/special_issues/intuitionistic_fuzzy_sets (accessed on 19 December 2023).

Smarandache F. Neutrosophy/Neutrosophic Probability, Set, and Logic, Proquest Information and Learning. Ann Arbor; 1998.

Mendel JM. Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions. Prentice-Hall; 2001.

Zadeh LA. The concept of a linguistic variable and its application to approximate reasoning—I. Information Sciences. 1975, 8(3): 199-249. doi: 10.1016/0020-0255(75)90036-5

Mohammadzadeh A, Zhang C, Alattas KA, et al. Fourier-based type-2 fuzzy neural network: Simple and effective for high dimensional problems. Neurocomputing. 2023, 547: 126316. doi: 10.1016/j.neucom.2023.126316

Cao Y, Raise A, Mohammadzadeh A, et al. Deep learned recurrent type-3 fuzzy system: Application for renewable energy modeling/prediction. Energy Reports. 2021, 7: 8115-8127. doi: 10.1016/j.egyr.2021.07.004

Mohammadzadeh A, Sabzalian MH, Zhang W. An Interval Type-3 Fuzzy System and a New Online Fractional-Order Learning Algorithm: Theory and Practice. IEEE Transactions on Fuzzy Systems. 2020, 28(9): 1940-1950. doi: 10.1109/tfuzz.2019.2928509

Kaufmann AK, Gupta MM. Introduction to Fuzzy Arithmetic: Theory and Applications. Van Nostrand Reinhold Company; 1991.

Dubois D, Prade H. Interval-valued fuzzy sets, possibility theory and imprecise probability. In: Proceedings of the Joint 4th Conference of the European Society for Fuzzy Logic and Technology and the 11th Rencontres Francophones sur la Logique Floue et ses Applications; 7–9 September 2005; Barcelona, Spain. pp. 314-319.

Pawlak Z. Rough Sets: Aspects of Reasoning about Data. Kluer Academic Publishers; 1991.

Deng J. Control problems of grey systems. Systems and Control Letters. 1982, 1(5): 288-294.

Maji PK, Biswas R, Roy AR. Soft set theory. Computers & Mathematics with Applications. 2003, 45(4-5): 555-562. doi: 10.1016/s0898-1221(03)00016-6

Maji PK, Roy AR, Biswas R. An application of soft sets in a decision-making problem. Computers & Mathematics with Applications. 2002, 44(8-9): 1077-1083. doi: 10.1016/s0898-1221(02)00216-x

Voskoglou MGr. Fuzziness, Indeterminacy and Soft Sets: Frontiers and Perspectives. Mathematics. 2022, 10(20): 3909. doi: 10.3390/math10203909

Voskoglou MGr. Neutrosophic Assessment and Decision Making. Equations. 2023, 3: 68-72.

Willard S. General Topology. Dover Publications; 2004.

Chang CL. Fuzzy topological spaces. Journal of Mathematical Analysis and Applications. 1968, 24(1): 182-190. doi: 10.1016/0022-247x(68)90057-7

Luplanlez FG. On Intuitionistic Fuzzy Topological Spaces. Kybernetes. 2006, 35(5): 743-747.

Salama AA, Alblowi SA. Neutrosophic Sets and Neutrosophic Topological Spaces. IOSR Journal of Mathematics. 2013, 3(4): 31-35.

Shabir M, Naz M. On soft topological spaces. Computers & Mathematics with Applications. 2011, 61(7): 1786-1799. doi: 10.1016/j.camwa.2011.02.006

Dan S, et al. Intuitionistic Type-2 Fuzzy Set and Its Properties. Symmetry. 2019, 11: 808.

Castillo O, Melin P. Towards Interval Type-3 Intuitionistic Fuzzy Sets and Systems. Mathematics. 2022, 10(21): 4091. doi: 10.3390/math10214091

Castillo O, Castro JR, Melin P. Interval Type-3 Fuzzy Control for Automated Tuning of Image Quality in Televisions. Axioms. 2022, 11(6): 276. doi: 10.3390/axioms11060276

Published
2023-12-12
How to Cite
Voskoglou, M. G. (2023). Applications of intuitionistic fuzzy sets to assessment, decision making and to topological spaces. Journal of AppliedMath, 1(4), 325. https://doi.org/10.59400/jam.v1i4.325
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