International Journal of Fuzzy Logic and Intelligent Systems 2021; 21(3): 233-242
Published online September 25, 2021
https://doi.org/10.5391/IJFIS.2021.21.3.233
© The Korean Institute of Intelligent Systems
Muhammad Ihsan1, Atiqe Ur Rahman1, Muhammad Saeed1, and Hamiden Abd El-Wahed Khalifa2
1Department of Mathematics, University of Management and Technology, Lahore, Pakistan
2Department of Mathematics, College of Science and Arts, Qassim University, Al-Badaya, Saudi Arabia
Correspondence to :
Muhammad Ihsan (mihkhb@gmail.com)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Molodtsov presented the idea of the soft set theory as a universal scientific apparatus for the provisioning of a parameterization tool. Alkhazaleh and Salleh (2011) characterized the idea of soft expert sets in which the client can understand the assessment of specialists in a single pattern and allow the use of this idea for dynamic issues. In this study, we summarize the idea of a soft expert set to fuzzy soft expert set, which will be progressively viable and helpful. The idea of convex and concave sets is crucial for optimization and related theories. In this investigation, convex and concave fuzzy soft expert sets are characterized first, and a portion of their significant properties are then discussed.
Keywords: Soft set, Fuzzy soft set, Soft expert set, Convex fuzzy soft expert set, Concave fuzzy soft expert set
No potential conflicts of interest relevant to this article are reported.
E-mail: mihkhb@gmail.com
E-mail: aurkhb@gmail.com
E-mail: muhammad.saeed@umt.edu.pk
E-mail: hamiden@cu.edu.eg; ha.ahmed@qu.edu.sa
International Journal of Fuzzy Logic and Intelligent Systems 2021; 21(3): 233-242
Published online September 25, 2021 https://doi.org/10.5391/IJFIS.2021.21.3.233
Copyright © The Korean Institute of Intelligent Systems.
Muhammad Ihsan1, Atiqe Ur Rahman1, Muhammad Saeed1, and Hamiden Abd El-Wahed Khalifa2
1Department of Mathematics, University of Management and Technology, Lahore, Pakistan
2Department of Mathematics, College of Science and Arts, Qassim University, Al-Badaya, Saudi Arabia
Correspondence to:Muhammad Ihsan (mihkhb@gmail.com)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Molodtsov presented the idea of the soft set theory as a universal scientific apparatus for the provisioning of a parameterization tool. Alkhazaleh and Salleh (2011) characterized the idea of soft expert sets in which the client can understand the assessment of specialists in a single pattern and allow the use of this idea for dynamic issues. In this study, we summarize the idea of a soft expert set to fuzzy soft expert set, which will be progressively viable and helpful. The idea of convex and concave sets is crucial for optimization and related theories. In this investigation, convex and concave fuzzy soft expert sets are characterized first, and a portion of their significant properties are then discussed.
Keywords: Soft set, Fuzzy soft set, Soft expert set, Convex fuzzy soft expert set, Concave fuzzy soft expert set
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