Fuzzy Parameterized Complex Multi-Fuzzy Soft Expert Set in Prediction of Coronary Artery Disease
In this work, state the risk and treatment of coronary artery disease our aim. The weighted fuzzy parameterized complex multi-fuzzy soft expert set plays the main roads to arrive a maple treatment. We take a reality values of the a asymptotes systolic blood pressure, lowdensity lipoprotein cholesterol, maximum heart rate, blood sugar, old peak and age of nine patients and transform by FORTRAN program to weighted fuzzy parameterized complex multifuzzy soft expert set. By Kong algorithm state the positive and negative decision, from these decisions state the degree of risk and treatments. Our decision helps the hospital doctor to state the treatments drug therapy or intervention.
2. Atanassov, K.T. Intuitionistic fuzzy sets. Fuzzy Sets Syst. 1986, 20, 87–96.
3. Sebastian, S.Ramakrishnan, T.V. Multi-fuzzy sets. Int. Math. Forum 2010, 5, 2471–2476.
4. Sebastian, S.Ramakrishnan, T.V. Multi-fuzzy sets: An extension of fuzzy sets. Fuzzy Inf. Eng. 2011, 3, 35–43.
5. Lukovac, V.Popovi´c, M. Fuzzy Delphi approach to defining a cycle for assessing the performance of military drivers. Decis. Mak. Appl. Manag. Eng. 2018, 1, 67–81.
6. Stanujkic, D.; Karabaševi´c, D. An extension of the WASPAS method for decision-making problems with intuitionistic fuzzy numbers: a case of website evaluation. Oper. Res. Eng. Sci. Theory Appl. 2018, 1, 29–39.
7. Molodtsov, D. Soft set theory—First results. Comput. Math. Appl. 1999, 37, 19–31.
8. Maji, P.K.; Biswas, R.; Roy, A.R. Fuzzy soft set theory. J. Fuzzy Math. 2001, 9, 589–602.
9. Alcantud, J.; Muñoz Torrecillas, M. Intertemporal Choice of Fuzzy Soft Sets. Symmetry 2018, 10, 371.
10. Maji, P.K.; Biswas, R.; Roy, A.R. Intuitionistic fuzzy soft sets. J. Fuzzy Math. 2001, 9, 677–692.
11. Garg, H.; Arora, R. Generalized intuitionistic fuzzy soft power aggregation operator based on t-norm and their application in multi criteria decision-making. Int. J. Intell. Syst. 2018, 34, 215–246.
12. Yang, Y.Tan, X.;Meng, C. The multi-fuzzy soft set and its application in decision making. Appl. Math. Model. 2013, 37, 4915–4923.
13. Alkhazaleh, S.Salleh, A.R. Soft expert sets. Adv. Decis. Sci. 2011, 2011, 757868.
14. Alkhazaleh, S.Salleh, A.R. Fuzzy soft expert set and its application. Appl. Math. 2014, 5, 1349–1368.
15. Al-Qudah, Y.Hassan, N. Bipolar fuzzy soft expert set and its application in decision making. Int. J. Decis. Sci. 2017, 10, 175–191.
16. Adam, F.; Hassan, N. Multi Q-fuzzy parameterized soft set and its application. J. Intell. Fuzzy Syst. 2014, 27, 419–424.
17. Ulucay, V.¸Sahin, M.Hassan, N. Generalized neutrosophic soft expert set for multiple-criteria decision-making. Symmetry 2018, 10, 437.
18. Abu Qamar, M.Hassan, N. Generalized Q-neutrosophic soft expert set for decision under uncertainty. Symmetry 2018, 10, 621.
19. Ramot, D.; Milo, R.; Friedman, M.Kandel, A. Complex fuzzy sets. IEEE Trans Fuzzy Syst. 2002,
20. Ramot, D.; Friedman, M.Langholz, G.; Kandel, A. Complex fuzzy logic. IEEE Trans Fuzzy Syst. 2003, 11, 450–461.
21. Singh, P.K. Granular-based decomposition of complex fuzzy context and its analysis. Prog. Artif. Intell. 2019, 1–13.
22. Singh, P.K. Bipolar d-equal complex fuzzy concept lattice with its application. Neural Comput. Appl. 2019, 1–18.
23. Al-Qudah, Y.Hassan, N. Operations on complex multi-fuzzy sets. J. Intell. Fuzzy Syst. 2017, 33, 1527–1540.
24. Al-Qudah, Y.Hassan, N. Complex multi-fuzzy soft set: Its entropy and similarity measure. IEEE Access 2018, 6, 65002–65017.
25. Al-Qudah, Y.Hassan, N. Complex multi-fuzzy soft expert set and its application. Int. J. Math. Comput. Sci. 2019, 14, 149–176.
26. Çagman, N.Çitak, F.; Engino˘ glu, S. FP-soft set theory and its applications. Ann. Fuzzy Math. Inform. 2011, 2, 219–226.
27. Cagman, N.Citak, F.; Engino˘ glu, S. Fuzzy parameterised fuzzy soft set theory and its applications. Turk. J. Fuzzy Syst. 2010, 1, 21–35.
28. Deli, I.Cagman, N. Intuitionistic fuzzy parameterized soft set theory and its decision making. Appl. Soft Comput. 2015, 28, 109–113.
29. Deli, I.Karatas, S. Interval valued intuitionistic fuzzy parameterized soft set theory and its decision making. J. Intell. Fuzzy. Syst. 2016, 30, 2073–2082.
30. Bashir, M.Salleh, A.R. Fuzzy parameterized soft expert set. Abstr. Appl. Anal. 2012, 2012, 258361.
31. Hazaymeh, A.Abdullah, I.B.; Balkhi, Z.; Ibrahim, R. Fuzzy parameterized fuzzy soft expert set. Appl. Math. Sci. 2012, 6, 5547–5564.
32. Belov, A.Y.Borisenko, V.V.Latyshev, V.N. Monomial algebras. J. Math. Sci. 1997, 87, 3463–3575.
33. Belov, A.Y.Ivanov, I.A. Construction of semigroups with some exotic properties. Acta Appl. Math. 2005, 85, 49–56.
34. Ivanov-Pogodaev, I.Malev, S.Sapir, O. A construction of a finitely presented semigroup containing an infinite square-free ideal with zero multiplication. Int. J. Algebra Comput. 2018, 28, 1565–1573.
35. Youssef Al-Qudah, Mazlan Hassan and Nasruddin Hassan, Fuzzy Parameterized Complex Multi-Fuzzy Soft Expert Set theory and its application in decision-making, Symmetry 2019, 11, 358
Copyright (c) 2020 Journal of Progressive Research in Mathematics
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.