Novel Neutrosophic Cubic Graphs Structures With Application In Decision Making Problems


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Novel Neutrosophic Cubic Graphs Structures with Application in Decision Making Problems


Novel Neutrosophic Cubic Graphs Structures with Application in Decision Making Problems

Author: Muhammad Gulistan

language: en

Publisher: Infinite Study

Release Date:


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Graphs allows us to study the different patterns of inside the data by making a mental image. The aim of this paper is to develop neutrosophic cubic graph structure which is the extension of neutrosophic cubic graphs. As neutrosophic cubic graphs are defined for one set of edges between vertices while neutrosophic cubic graphs structures are defined for more than one set of edges. Further, we defined some basic operations such as Cartesian product, composition, union, join, cross product, strong product and lexicographic product of two neutrosophic cubic graph structures. Several types of other interesting properties of neutrosophic cubic graph structures are discussed in this paper. Finally, a decision-making algorithm based on the idea of neutrosophic cubic graph structures is constructed. The proposed decision-making algorithm is applied in a decision-making problem to check the validity.

Novel Neutrosophic Cubic Graphs Structures with Application in Decision Making Problems


Novel Neutrosophic Cubic Graphs Structures with Application in Decision Making Problems

Author: Muhammad Gulistan

language: en

Publisher: Infinite Study

Release Date:


DOWNLOAD





Graphs allows us to study the different patterns of inside the data by making a mental image. The aim of this paper is to develop neutrosophic cubic graph structure which is the extension of neutrosophic cubic graphs. As neutrosophic cubic graphs are defined for one set of edges between vertices while neutrosophic cubic graphs structures are defined for more than one set of edges. Further, we defined some basic operations such as Cartesian product, composition, union, join, cross product, strong product and lexicographic product of two neutrosophic cubic graph structures. Several types of other interesting properties of neutrosophic cubic graph structures are discussed in this paper. Finally, a decision-making algorithm based on the idea of neutrosophic cubic graph structures is constructed. The proposed decision-making algorithm is applied in a decision-making problem to check the validity.

A study of plithogenic graphs: applications in spreading coronavirus disease (COVID-19) globally


A study of plithogenic graphs: applications in spreading coronavirus disease (COVID-19) globally

Author: Fazeelat Sultana

language: en

Publisher: Infinite Study

Release Date: 2023-01-01


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During the last two decades, the world has experienced three major outbreaks of Coronaviruses, namely severe acute respiratory syndrome (SARS- CoV), middle east respiratory syndrome (MERS-CoV), and the current ongoing pandemic of severe acute respiratory syndrome 2 (SARS-CoV-2). The SARS-CoV-2 caused the disease known as Coronavirus Disease 2019 (COVID-19). Since its discovery for the first time in Wuhan, China, in December 2019, the disease has spread very fast, and cases have been reported in more than 200 countries/territories. In this study, the idea of Smarandache’s pathogenic set is used to discuss the novel COVID-19 spread. We first introduced plithogenic graphs and their subclass, like plithogenic fuzzy graphs. We also established certain binary operations like union, join, Cartesian product, and composition of pathogenic fuzzy graphs, which are helpful when we discuss combining two different graphs. In the end, we investigate the spreading trend of COVID-19 by applying the pathogenic fuzzy graphs. We observe that COVID-19 is much dangerous than (MERS-CoV) and (SARS-CoV). Moreover, as the SARS-CoV and MERS-CoV outbreaks were controlled, there are greater chances to overcome the current pandemic of COVID-19 too. Our model suggests that all the countries should stop all types of traveling/movement across the borders and internally too to control the spread of COVID-19. The proposed model also predicts that in case precautionary measures have not been taken then there is a chance of severe outbreak in future.