Utilization of interval-valued intuitionistic fuzzy soft set in the health sector
Keywords:
soft set, intuitionistic fuzzy soft set, interval-valued intuitionistic fuzzy soft set, restricted union, restricted intersectionAbstract
The soft set theory plays a key role for dealing with uncertainty, fuzziness and vagueness. The concept of fuzzy soft set which can be seen as a new mathematical approach to vagueness is used in many applications including reliability evaluation, multi criteria decision making and medical diagnosis problems. Later, it is generalized to an interval-valued intuitionistic fuzzy soft set. In this attempt we present the definition and operations of an interval-valued intuitionistic fuzzy soft set. Furthermore, based on the analysis of several operations on interval-valued intuitionistic fuzzy soft set in the study, we provide some notions such as the restricted intersection and restricted union of two interval-valued intuitionistic fuzzy soft sets for selection of appropriate hospital for patient affected by specific dieses.
Downloads
References
Ali, M. I., Feng, F., Liu, X., Min ,W.K. & Shabir, M.(2009). On some new operations in soft set theory. Computers & Mathematics with Applications, 57 , 1547-1553.
Alkhazaleh, S., Salleh,A. R. & Hassan, N. (2011). Fuzzy parameterized interval-valued fuzzy soft set. Applied Mathematical Sciences, 67 , 3335-3346.
Alkhazaleh. S., Salleh, A. R. & Hassan, N.(2011). Soft multisets theory. Applied Mathematical Sciences, 72 , 3561-3573.
Atanassov, K. & Gargov, G.(1989). Interval valued intuitionistic fuzzy sets. Fuzzy Sets and Systems, 31, 343-349.
Atanassov, K.(1994). Operators over interval valued intuitionistic fuzzy sets. Fuzzy Sets and Systems, 64 ,159-174.
Atanassov, K.T. (1986). Intuitionistic fuzzy set. Fuzzy Sets and Systems, 20 , 87-96.
Deschrijver,G. & Kerre, E.F. (2003). On the relationship between some extensions of fuzzy set theory. Fuzzy Sets and Systems, 133, 227- 235.
Gandamayu, I. B. M., Antari, N. W. S., & Strisanti, I. A. S. (2022). The level of community compliance in implementing health protocols to prevent the spread of COVID-19. International Journal of Health & Medical Sciences, 5(2), 177-182. https://doi.org/10.21744/ijhms.v5n2.1897
Gorzalczany, M. B. (1987). A method of inference in approximate reasoning based on interval valued fuzzy sets. Fuzzy Sets and Systems, 21, 1-17.
Jiang,Y., Tang,Y., Chen, Q., Liu, H. & Tanga, J. (2010) Interval-valued intuitionistic fuzzy soft sets and their properties, Computers and Mathematics with Applications, 60, 906-918.
Kong, Z., Gao, L. & Wang, L. (2009). Comment on A fuzzy soft set theoretic approach to decision making problems. Journal Computer Appl. Math. 223 , 540-542.
Kong, Z., Gao, L., Wang, L., & Li,S. (2008). The normal parameter reduction of soft sets and its algorithm. Comput. Math. Appl, 56 , 3029-3037.
Maji, P. K., Biswas,R. & Roy, A. R.(2001). Intuitionistic fuzzy soft sets. Journal of Fuzzy Mathematics, 9 , 677- 692.
Maji, P. K., Biswas,R. & Roy, A.R.(2003). Soft set theory. Comput. Math. Appl, 45 , 555-562.
Maji, P. K., Roy, A.R. & Biswas, R. (2004). On intuitionistic fuzzy soft sets. Journal of Fuzzy Mathematics, 12 669-683.
Molodtsov, D. (1999). Soft set theory first result. An International Journal of Computers and mathematics with Applications, 37, 19-31.
Pawlak, Z.(1991). Rough Sets: Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers.
Pinoargote, J. A. P., Alcivar, J. T. R., & Viteri, C. G. V. (2018). Analysis and design of wastewater treatment. International Journal of Life Sciences, 2(3), 121–135. https://doi.org/10.29332/ijls.v2n3.221
Suryasa, I. W., Rodríguez-Gámez, M., & Koldoris, T. (2021). Health and treatment of diabetes mellitus. International Journal of Health Sciences, 5(1), i-v. https://doi.org/10.53730/ijhs.v5n1.2864
Xu,W., Ma,J., Wang, S. & Hao,G. (2010). Vague soft sets and their properties. Computers & Mathematics with Applications, 59 ,787-794.
Xu,Y., Sun Y., & Li, D. (2010). Intuitionistic fuzzy soft set. Science & Research Department Dalian Naval Academy Dalian China,
Yang, X. B., Lin,T.Y., Yang, J.Y., Li,Y. & Yu, D. (2009). Combination of interval-valued fuzzy set and soft set. Computers & Mathematics with Applications, 58 521-527.
Yao, B., Jin-liang, L.& Rui-xia,Y. (2008). Fuzzy soft set and soft fuzzy set. Fourth International Conference on Natural Computation, 4 , 252-255.
Zadeh,L. A.(1965). Fuzzy sets. Information and Control, 8 , 338-353.
Published
How to Cite
Issue
Section
Copyright (c) 2022 International journal of health sciences

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Articles published in the International Journal of Health Sciences (IJHS) are available under Creative Commons Attribution Non-Commercial No Derivatives Licence (CC BY-NC-ND 4.0). Authors retain copyright in their work and grant IJHS right of first publication under CC BY-NC-ND 4.0. Users have the right to read, download, copy, distribute, print, search, or link to the full texts of articles in this journal, and to use them for any other lawful purpose.
Articles published in IJHS can be copied, communicated and shared in their published form for non-commercial purposes provided full attribution is given to the author and the journal. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
This copyright notice applies to articles published in IJHS volumes 4 onwards. Please read about the copyright notices for previous volumes under Journal History.








