双宇宙上直觉模糊关系的线性二叉模糊集的粗糙度与决策应用

Rizwan Gul, Saba Ayub, Muhammad Shabir, Tmader Alballa, Hamiden Abd El-Wahed Khalifa
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引用次数: 0

摘要

粗糙集(RS)和模糊集(FS)旨在解决数据的不确定性问题。通过考虑控制或参考参数,线性二叉模糊集(LD-FS)是决策制定(DM)的一种新方法,它拓宽了以前占主导地位的直觉模糊集(IFS)、毕达哥拉斯模糊集(PyFS)和q-rung正交模糊集(q-ROFS)理论,并允许更灵活地表示不确定数据。在 LD-FS 的背景下研究 RS,即用直觉模糊关系(IFR)来近似 LD-FS 是 RS 理论的一个有前途的途径。本文的主要目标是为 LD-FSs 创建一种新的粗糙度方法,该方法采用了双宇宙上的直觉模糊关系。本文利用 IFR 建立了 LD-FS 的下近似和上近似概念,并对一些公理系统进行了细致研究。此外,还建立了 LD-FRS 与线性 Diophantine 模糊拓扑学(LDF-topology)之间的联系。最后,基于 LD-FRS 的下近似和上近似,研究了几种相似性关系。同时,我们将双宇宙上的 LD-FRS 推荐模型用于解决 DM 问题。此外,我们还给出了一个实际案例研究,以证明我们所设计方法的实用性和可行性。最后,我们与现有的一些方法进行了详细的比较分析,以探讨所建立技术的有效性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Roughness of linear Diophantine fuzzy sets by intuitionistic fuzzy relations over dual universes with decision-making applications

Rough sets (RSs) and fuzzy sets (FSs) are designed to tackle the uncertainty in the data. By taking into account the control or reference parameters, the linear Diophantine fuzzy set (LD-FS) is a novel approach to decision making (DM), broadens the previously dominant theories of the intuitionistic fuzzy set (IFS), Pythagorean fuzzy set (PyFS), and q-rung orthopair fuzzy set (q-ROFS), and allows for a more flexible representation of uncertain data. A promising avenue for RS theory is to investigate RSs within the context of LD-FS, where LD-FSs are approximated by an intuitionistic fuzzy relation (IFR). The major goal of this article is to create a novel method of roughness for LD-FSs employing an IFR over dual universes. The notions of lower and upper approximations of an LD-FS are established by using an IFR, and some axiomatic systems are carefully investigated in detail. Moreover, a link between LD-FRSs and linear Diophantine fuzzy topology (LDF-topology) has been established. Eventually, based on lower and upper approximations of an LD-FS, several similarity relations are investigated. Meanwhile, we apply the recommended model of LD-FRSs over dual universes for solving the DM problem. Furthermore, a real-life case study is given to demonstrate the practicality and feasibility of our designed approach. Finally, we conduct a detailed comparative analysis with certain existing methods to explore the effectiveness and superiority of the established technique.

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来源期刊
自引率
11.50%
发文量
352
期刊介绍: Computational & Applied Mathematics began to be published in 1981. This journal was conceived as the main scientific publication of SBMAC (Brazilian Society of Computational and Applied Mathematics). The objective of the journal is the publication of original research in Applied and Computational Mathematics, with interfaces in Physics, Engineering, Chemistry, Biology, Operations Research, Statistics, Social Sciences and Economy. The journal has the usual quality standards of scientific international journals and we aim high level of contributions in terms of originality, depth and relevance.
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