Conflict distance-based variable precision Pythagorean fuzzy rough set in Pythagorean fuzzy decision systems with applications in decision making
Volume 34, Issue 1, pp 65--73
https://dx.doi.org/10.22436/jmcs.034.01.06
Publication Date: February 16, 2024
Submission Date: November 27, 2023
Revision Date: December 11, 2023
Accteptance Date: December 13, 2023
Authors
L. Sahoo
- Department of Computer and Information Science, Raiganj University, Raiganj 733134, India.
S. Guchhait
- Department of Computer Science, Tamralipta Mahavidyalaya, Tamluk, W.B-721636, India.
T. Allahviranloo
- Research Center of Performance and Productivity Analysis, Istinye University, Istanbul, Turkiye.
J. R. R. Kumar
- Computer Engineering Department, Genba Sopanrao Moze College of Engineering, Pune, India.
M. R. Tarambale
- Electrical Engineering Department, PVG’s College of Engineering and Technology and G K Pate Institute of Management, Pune, India.
M. Catak
- College of Engineering and Technology, American University of the Middle East, Kuwait.
Abstract
Our main task in this paper is to consider a type of nonlinear Volterra integral equations (NVIE) for the existence and uniqueness of the solution and stability of this equations. In this article, considering the fuzzy space in matrix form has tried to select the optimal controller for the control function. For this purpose, by using several types of special functions and by introducing the aggregation function, we investigate the optimal stability of the NVI equations. We also present an application of the obtained results numerically.
Share and Cite
ISRP Style
L. Sahoo, S. Guchhait, T. Allahviranloo, J. R. R. Kumar, M. R. Tarambale, M. Catak, Conflict distance-based variable precision Pythagorean fuzzy rough set in Pythagorean fuzzy decision systems with applications in decision making, Journal of Mathematics and Computer Science, 34 (2024), no. 1, 65--73
AMA Style
Sahoo L., Guchhait S., Allahviranloo T., Kumar J. R. R., Tarambale M. R., Catak M., Conflict distance-based variable precision Pythagorean fuzzy rough set in Pythagorean fuzzy decision systems with applications in decision making. J Math Comput SCI-JM. (2024); 34(1):65--73
Chicago/Turabian Style
Sahoo, L., Guchhait, S., Allahviranloo, T., Kumar, J. R. R., Tarambale, M. R., Catak, M.. "Conflict distance-based variable precision Pythagorean fuzzy rough set in Pythagorean fuzzy decision systems with applications in decision making." Journal of Mathematics and Computer Science, 34, no. 1 (2024): 65--73
Keywords
- Fixed-point theory (FPT)
- Fuzzy optimal stability
- aggregation function (AF)
- Optimal control function
- nonlinear Volterra integral equation
MSC
- 46L05
- 47B47
- 47H10
- 46L57
- 39B62
References
-
[1]
M. Akram, I. Ullah, T. Allahviranloo, S. A. Edalatpanah, Fully Pythagorean fuzzy linear programming problems with equality constraints, Comput. Appl. Math., 40 (2021), 30 pages
-
[2]
M. Akram, I. Ullah, T. Allahviranloo, S. A. Edalatpanah, LR-type fully Pythagorean fuzzy linear programming problems with equality constraints, J. Intell. Fuzzy Syst., 41 (2021), 1975–1992
-
[3]
K. Atanassove, Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20 (1986), 87–96
-
[4]
D. C¸ oker, Fuzzy rough sets are intuitionistic L-fuzzy sets, Fuzzy Sets and Systems, 96 (1998), 381–383
-
[5]
C. Cornelis, M. D. Cock, E. E. Kerre, Intuitionistic fuzzy rough sets: at the crossroads of imperfect knowledge, Expert Syst., 20 (2003), 260–270
-
[6]
K. Das, S. Samanta, M. Pal, Study on centrality measures in social networks: a survey, Soc. Netw. Anal. Min., 8 (2018), 1–11
-
[7]
D. Dubois, H. Prade, Rough fuzzy sets and fuzzy rough sets, Int. J. General Syst., 17 (1990), 191–209
-
[8]
Y. Liu, Y. Lin, Intuitionistic fuzzy rough set model based on conflict distance and applications, Appl. Soft Comput., 31 (2015), 266–273
-
[9]
Y. Liu, Y. Lin, H. Zhao, Variable precision intuitionistic fuzzy rough set model and applications based on conflict distance, Expert Syst., 32 (2015), 220–227
-
[10]
R. Mahapatra, S. Samanta, M. Pal, Generalized neutrosophic planar graphs and its application, J. Appl. Math. Comput., 65 (2021), 693–712
-
[11]
P. Mandal, A. S. Ranadive, Decision-theoretic rough sets under Pythagorean fuzzy information, Int. J. Intell. Syst., 33 (2018), 818–835
-
[12]
P. Mandal, A. S. Ranadive, Pythagorean fuzzy preference relations and their applications in group decision-making systems, Int. J. Intell. Syst., 34 (2019), 1700–1717
-
[13]
P. Mandal, A. S. Ranadive, Multi-granulation Pythagorean fuzzy decision-theoretic rough sets based on inclusion measure and their application in incomplete multi-source information systems, Complex Intell. Syst., 5 (2019), 145–163
-
[14]
P. Mandal, S. Samanta, M. Pal, Large-scale alternative processing group decision-making under Pythagorean linguistic preference environment, Soft Comput., (2023), 1–14
-
[15]
P. Mandal, S. Samanta, M. Pal, A. S. Ranadive, Pythagorean linguistic preference relations and their applications to group decision making using group recommendations based on consistency matrices and feedback mechanism, Int. J. Intell. Syst., 35 (2020), 826–849
-
[16]
Z. Pawlak, Rough set, Internat. J. Comput. Inform. Sci., 11 (1982), 341–356
-
[17]
T. Pramanik, S. Samanta, M. Pal, Interval-valued fuzzy planar graphs, Int. J. Mach. Learn. Cybern., 7 (2016), 653–664
-
[18]
S. Samanta, M. Akram, M. Pal, m-step fuzzy competition graphs, J. Appl. Math. Comput., 47 (2015), 461–472
-
[19]
S. Samanta, M. Pal, Fuzzy k-competition graphs and p-competition fuzzy graphs, Fuzzy Inf. Eng., 5 (2013), 191–204
-
[20]
S. Samanta, M. Pal, Fuzzy planar graphs, IEEE Trans. Fuzzy Syst., 23 (2015), 1936–1942
-
[21]
S. Samanta, T. Pramanik, M. Pal, Fuzzy colouring of fuzzy graphs, Afr. Mat., 27 (2016), 37–50
-
[22]
B. Sun, S. Tong, W. Ma, T. Wang, C. Jiang, An approach to MCGDM based on multi-granulation Pythagorean fuzzy rough set over two universes and its application to medical decision problem, Artif. Intell. Rev., 55 (2022), 1887–1913
-
[23]
R. R. Yager, Pythagorean membership grades in multicriteria decision making, IEEE Trans. Fuzzy Syst., 22 (2014), 958– 965
-
[24]
R. R. Yager, A. M. Abbasov, Pythagorean membership grades, complex numbers, and decision making, Int. J. Intell. Syst., 28 (2013), 436–552
-
[25]
C. Yan, H. Zhang, Attribute Reduction Methods Based on Pythagorean Fuzzy Covering Information Systems, IEEE Access, 8 (2020), 28484–28495
-
[26]
C. Zhang, D. Li, R. Ren, Pythagorean fuzzy multigranulation rough set over two universes and its applications in merger and acquisition, Int. J. Intell. Syst., 31 (2016), 921–943
-
[27]
H. Zhang, Q. Ma, Three-way decisions with decision-theoretic rough sets based on Pythagorean fuzzy covering, Soft Comput., 24 (2020), 18671–18688
-
[28]
X. L. Zhang, Z. S. Xu, Extension of TOPSIS to multiple criteria decision making with Pythagorean fuzzy sets, Int. J. Intell. Syst., 29 (2014), 1061–1078
-
[29]
L. Zhou, W.-Z. Wu, W.-X. Zhang, On characterization of intuitionistic fuzzy rough sets based on intuitionistic fuzzy applicators, Inf. Sci., 179 (2009), 883–898