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Rizwan Gul 한국지능시스템학회 2022 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.22 No.3
The rough set (RS) theory is a successful approach for studying the uncertainty in data. Incontrast, the bipolar soft sets (BSS) can deal with the uncertainty, as well as bipolarity ofthe data in many situations. In 2018, Karaaslan and C¸ agman proposed bipolar soft rough ˘sets (BSRSs), a hybridization of RS and BSS. However, certain shortcomings with BSRSviolate Pawlak’s RS theory. To overcome these shortcomings, the concept of the modifiedbipolar soft rough set (MBSRS) has been proposed in this study. Moreover, this idea hasbeen investigated through illustrative examples, where the important properties are inspecteddeeply. Furthermore, certain significant measures associated with MBSRS are also provided. Finally, an application of the MBSRS to multi-attribute group decision-making (MAGDM)problems is proposed. In addition, among various alternatives, an algorithm for decisionmaking accompanied by a practical example is presented as the optimal alternative . A briefcomparative analysis of the proposed approach with some existing techniques is also providedto indicate the validity, flexibility, and superiority of the suggested MAGDM model.
Bipolar fuzzy soft sets in Γ-semirings
Yildiray Celik 원광대학교 기초자연과학연구소 2017 ANNALS OF FUZZY MATHEMATICS AND INFORMATICS Vol.13 No.1
In this paper, we have introduced the concept of bipolar fuzzy soft $\Gamma-$subsemiring and bipolar fuzzy soft $\Gamma-$ideal in a $\Gamma-$semiring. Also we study some of their algebraic properties. It is also proved that the collection of all bipolar fuzzy soft $\Gamma-$ideals over a $\Gamma-$semiring forms a complete distributive lattice with the special union and intersection.
Fuzzy Parameterized Bipolar Fuzzy Soft Expert Set and Its Application in Decision Making
Muhammad Ibrar,Asghar Khan,Sajjad Khan,Fatima Abbas 한국지능시스템학회 2019 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.19 No.4
In this paper, we present the study of fuzzy parameterized bipolar fuzzy soft expert sets and define some of its basic operations. We validated the basic properties and essential laws related to this methodology. Lastly, we presented some possible applications in decision-making problems using a generalized algorithm.