Novel Concepts on Domination in Neutrosophic Incidence Graphs with Some Applications

IF 0.7 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Siti Nurul Fitriah Mohamad, Roslan Hasni, Florentin Smarandache
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引用次数: 0

Abstract

In graph theory, the concept of domination is essential in a variety of domains. It has broad applications in diverse fields such as coding theory, computer network models, and school bus routing and facility location problems. If a fuzzy graph fails to obtain acceptable results, neutrosophic sets and neutrosophic graphs can be used to model uncertainty correlated with indeterminate and inconsistent information in arbitrary real-world scenario. In this study, we consider the concept of domination as it relates to single-valued neutrosophic incidence graphs (SVNIGs). Given the importance of domination and its utilization in numerous fields, we propose the application of dominating sets in SVNIG with valid edges. We present some relevant definitions such as those of valid edges, cardinality, and isolated vertices in SVNIG along with some examples. Furthermore, we also show a few significant sets connected to the dominating set in an SVNIG such as independent and irredundant sets. We also investigate a relationship between the concepts of dominating sets and domination numbers as well as irredundant and independence sets in SVNIGs. Finally, a real-life deployment of domination in SVNIGs is investigated in relation to COVID-19 vaccination locations as a practical application.
中性粒细胞关联图中控制的新概念及其应用
在图论中,支配的概念在许多领域都是必不可少的。它在编码理论、计算机网络模型、校车路线和设施选址问题等各个领域都有广泛的应用。如果模糊图不能获得可接受的结果,中性集和中性图可以用来模拟任意现实场景中与不确定和不一致信息相关的不确定性。在本研究中,我们考虑支配的概念,因为它与单值嗜中性粒细胞发生率图(SVNIGs)有关。鉴于支配集的重要性及其在许多领域的应用,我们提出了支配集在具有有效边的SVNIG中的应用。我们给出了SVNIG中有效边、基数和孤立顶点的相关定义,并给出了一些示例。此外,我们还展示了一些与svig中的支配集相连的重要集,如独立集和非冗余集。我们还研究了svnig中支配集和支配数以及无冗余集和独立集的概念之间的关系。最后,作为实际应用,研究了与COVID-19疫苗接种地点相关的SVNIGs中的实际支配部署。
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来源期刊
CiteScore
1.50
自引率
14.30%
发文量
89
期刊介绍: JACIII focuses on advanced computational intelligence and intelligent informatics. The topics include, but are not limited to; Fuzzy logic, Fuzzy control, Neural Networks, GA and Evolutionary Computation, Hybrid Systems, Adaptation and Learning Systems, Distributed Intelligent Systems, Network systems, Multi-media, Human interface, Biologically inspired evolutionary systems, Artificial life, Chaos, Complex systems, Fractals, Robotics, Medical applications, Pattern recognition, Virtual reality, Wavelet analysis, Scientific applications, Industrial applications, and Artistic applications.
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