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Double-Valued Complex Neutrosophic Graphs, Suriyakumar G, V. J. Sudhakar, Takaaki Fujita Mar 2026

Double-Valued Complex Neutrosophic Graphs, Suriyakumar G, V. J. Sudhakar, Takaaki Fujita

Neutrosophic Systems with Applications

This paper introduces a novel graph-theoretic framework, called the double-valued complex neutrosophic graph, as an extension of double-valued neutrosophic set theory. Within this framework, we investigate several important classes of such graphs, including self-complementary, strong, and full double-valued complex neutrosophic graphs, and establish a number of their fundamental properties. To clarify the proposed concepts and demonstrate their structural behavior, several relevant illustrative examples are also provided.


Single-Valued, Double-Valued, Triple-Valued, Quadruple-Valued, And Quintuple-Valued Neutrosophic Graph, Takaaki Fujita, Arif Mehmood, Arkan A. Ghaib Feb 2026

Single-Valued, Double-Valued, Triple-Valued, Quadruple-Valued, And Quintuple-Valued Neutrosophic Graph, Takaaki Fujita, Arif Mehmood, Arkan A. Ghaib

Neutrosophic Systems with Applications

Concepts such as fuzzy sets, neutrosophic sets, rough sets, and plithogenic sets have been extensively studied as formal tools for modeling uncertainty, and they have found broad applications across many disciplines. A Double-Valued Neutrosophic Set (DVNS) extends the classical neutrosophic framework by splitting indeterminacy into two distinct components: one leaning toward truth and the other leaning toward falsity. In recent years, further refinements—namely Triple-Valued, Quadruple-Valued, and Quintuple-Valued Neutrosophic Sets—have also been introduced and investigated. These uncertainty models have naturally been lifted to graph-theoretic settings, where vertices and edges represent entities and relationships under ambiguity. Although fuzzy graphs and neutrosophic graphs …


Revisiting Bipolar Neutrosophic Graph And Interval-Valued Neutrosophic Graph, Takaaki Fujita Apr 2025

Revisiting Bipolar Neutrosophic Graph And Interval-Valued Neutrosophic Graph, Takaaki Fujita

Neutrosophic Systems with Applications

Graph theory explores networks composed of nodes (vertices) and their connections (edges). A graph class is a collection of graphs that share common structural properties, defined by specific rules or constraints. This paper examines various models of uncertain graphs, including Fuzzy, Intuitionistic Fuzzy , Neutrosophic, Turiyam Neutrosophic, and Plithogenic Graphs. In particular, this study focuses on Bipolar Graphs and Interval-valued Graphs, analyzing them within the frameworks of Fuzzy, Neutrosophic, Turiyam Neutrosophic, and Plithogenic Graphs.


Contact Graphs In Fuzzy And Neutrosophic Graphs, Takaaki Fujita Apr 2025

Contact Graphs In Fuzzy And Neutrosophic Graphs, Takaaki Fujita

Neutrosophic Systems with Applications

Graph Theory is a branch of mathematics dedicated to studying graphs, which depict relationships between objects through vertices and edges. A significant focus in this field is the study of contact graphs, where vertices correspond to sets, and edges represent intersections between those sets. To better model uncertainties in real-world situations, several graph types---such as fuzzy, neutrosophic, and Plithogenic graphs---have been developed. This paper investigates the concept of contact graphs within these frameworks, offering insights into their behavior under various uncertain conditions.


Some Graph Parameters For Superhypertree-Width And Neutrosophictree-Width, Takaaki Fujita, Florentin Smarandache Apr 2025

Some Graph Parameters For Superhypertree-Width And Neutrosophictree-Width, Takaaki Fujita, Florentin Smarandache

Neutrosophic Systems with Applications

Graph characteristics are often studied through various parameters, with ongoing research dedicated to exploring these aspects. Among these, graph width parameters—such as treewidth—are particularly important due to their practical applications in algorithms and real-world problems. A hypergraph generalizes traditional graph theory by abstracting and extending its concepts [77]. More recently, the concept of a SuperHyperGraph has been introduced as a further generalization of the hypergraph. Neutrosophic logic [133], a mathematical framework, extends classical and fuzzy logic by allowing the simultaneous consideration of truth, indeterminacy, and falsity within an interval. In this paper, we explore Superhypertree-width, Neutrosophic treewidth, and t-Neutrosophic tree-width.


A Reconsideration Of Advanced Concepts In Neutrosophic Graphs: Smart, Zero Divisor, Layered, Weak, Semi, And Chemical Graphs, Takaaki Fujita, Florentin Smarandache Apr 2025

A Reconsideration Of Advanced Concepts In Neutrosophic Graphs: Smart, Zero Divisor, Layered, Weak, Semi, And Chemical Graphs, Takaaki Fujita, Florentin Smarandache

Neutrosophic Systems with Applications

One of the most powerful tools in graph theory is the classification of graphs into distinct classes based on shared properties or structural features. Over time, many graph classes have been introduced, each aimed at capturing specific behaviors or characteristics of a graph. Neutrosophic Set Theory, a method for handling uncertainty, extends fuzzy logic by incorporating degrees of truth, indeterminacy, and falsity. Building on this framework, Neutrosophic Graphs [9, 84, 135] have emerged as significant generalizations of fuzzy graphs. In this paper, we extend several classes of fuzzy graphs to Neutrosophic graphs and analyze their properties.


Mixed Graph In Fuzzy, Neutrosophic, And Plithogenic Graphs, Takaaki Fujita, Florentin Smarandache Nov 2024

Mixed Graph In Fuzzy, Neutrosophic, And Plithogenic Graphs, Takaaki Fujita, Florentin Smarandache

Neutrosophic Sets and Systems

Graph theory examines networks consisting of nodes (vertices) and the connections (edges) between them. Mixed graphs, which combine both undirected and directed edges, provide a versatile framework for representing relationships with symmetric and asymmetric connections across various systems. In this work, we introduce and analyze the concept of mixed graphs within the contexts of Fuzzy Graphs, Neutrosophic Graphs, and Turiyam Neutrosophic Graphs. By exploring their properties, interrelations, and potential applications, we aim to advance theunderstanding of uncertain graphs.


A Review Of The Hierarchy Of Plithogenic, Neutrosophic, And Fuzzy Graphs: Survey And Applications, Takaaki Fujita, Florentin Smarandache Jan 2024

A Review Of The Hierarchy Of Plithogenic, Neutrosophic, And Fuzzy Graphs: Survey And Applications, Takaaki Fujita, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

As many readers may know, graph theory is a fundamental branch of mathematics that examines networks consisting of nodes and edges, with a focus on their paths, structures, and properties [157]. A Fuzzy Graph extends this concept by assigning a membership degree between 0 and 1 to each edge and vertex, capturing the level of uncertainty. Expanding on this idea, the Turiyam Neutrosophic Graph was introduced as an extension of both Neutrosophic and Fuzzy Graphs. Plithogenic graphs, in turn, offer a powerful approach for managing uncertainty. In this paper, we explore the relationships among various graph classes, including Plithogenic graphs, …


A Compact Exploration Of Turiyam Neutrosophic Competition Graphs, Takaaki Fujita, Florentin Smarandache Jan 2024

A Compact Exploration Of Turiyam Neutrosophic Competition Graphs, Takaaki Fujita, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Graph theory, a branch of mathematics, examines relationships between entities using vertices and edges. Within this field, Uncertain Graph Theory has emerged to model uncertainties in real-world networks. A notable concept in this area is the competition graph, which captures interactions by connecting vertices that “compete” for the same neighbor, represented by directed edges indicating common neighbors in a digraph. This brief paper introduces the concept of the Generalized Turiyam Neutrosophic Competition Graph and explores its relationships with other graph classes.


A Reconsideration Of Advanced Concepts In Neutrosophic Graphs: Smart, Zero Divisor, Layered, Weak, Semi, And Chemical Graphs, Takaaki Fujita, Florentin Smarandache Jan 2024

A Reconsideration Of Advanced Concepts In Neutrosophic Graphs: Smart, Zero Divisor, Layered, Weak, Semi, And Chemical Graphs, Takaaki Fujita, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

One of the most powerful tools in graph theory is the classification of graphs into distinct classes based on shared properties or structural features. Over time, many graph classes have been introduced, each aimed at capturing specific behaviors or characteristics of a graph. Neutrosophic Set Theory, a method for handling uncertainty, extends fuzzy logic by incorporating degrees of truth, indeterminacy, and falsity. Building on this framework, Neutrosophic Graphs [9,84,135] have emerged as significant generalizations of fuzzy graphs. In this paper, we extend several classes of fuzzy graphs to Neutrosophic graphs and analyze their properties.


Critical Success Factors Modelling In Operational Management And The Recovery Of Overdue Portfolio Of The Babahoyo Gad In The Municipal Market May 4, Miguel Francisco Galarza Villalba, Marielisa Stefanía Serrano Viteri, Inés Ramos Castro, Felipe Vera Díaz Jun 2020

Critical Success Factors Modelling In Operational Management And The Recovery Of Overdue Portfolio Of The Babahoyo Gad In The Municipal Market May 4, Miguel Francisco Galarza Villalba, Marielisa Stefanía Serrano Viteri, Inés Ramos Castro, Felipe Vera Díaz

Neutrosophic Sets and Systems

This paper aims to study the situation of the recovery of the overdue portfolio of the Babahoyo Municipal Decentralized Autonomous Government (MDAG) in the municipal market "4 de Mayo". The problem consists in the difficulties arose in tax collection by the municipal government´s employees to this market. In the present investigation neutrosophic cognitive maps are applied to assess the relationship between every pair of causes of this problem. For the evaluation, we count on five experts’ criteria. Because there exist some pairs of causes whose relationship are unknown, neutrosophic cognitive maps are used instead of the fuzzy ones, where symbol …