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Journal articles on the topic 'Fuzzy graphs'

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1

Havare, Özge Çolakoğlu. "On Thorny Fuzzy Graphs." International Journal of Fuzzy Mathematical Archive 13, no. 02 (2017): 213–17. http://dx.doi.org/10.22457/ijfma.v13n2a11.

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A thorny fuzzy graph which is analogous to the concept thorny graphs in crisp graph theory is defined. The degree of an edge in thorny fuzzy graphs is obtained. Also, the degree of an edge in fuzzy graph formed by this operation in terms of the degree of edges in the given fuzzy graphs in some particular cases is found. Moreover, it is proved that thorny fuzzy graph of effective fuzzy graph is effective.
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2

Ramesh, Obbu, and S. Sharief Basha. "An Intuitionistic Fuzzy Graph’s Signless Laplacian Energy." International Journal of Engineering & Technology 7, no. 4.10 (October 2, 2018): 892. http://dx.doi.org/10.14419/ijet.v7i4.10.26782.

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We are extending concept into the Intuitionistic fuzzy graph’ Signless Laplacian energy instead of the Signless Laplacian energy of fuzzy graph. Now we demarcated an Intuitionistic fuzzy graph’s Signless adjacency matrix and also an Intuitionistic fuzzy graph’s Signless Laplacian energy. Here we find the Signless Laplacian energy ‘s Intuitionistic fuzzy graphs above and below boundaries of an with suitable examples.
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3

Abebe Ashebo, Mamo, and V. N. Srinivasa Rao Repalle. "Fuzzy Chromatic Polynomial of Fuzzy Graphs with Crisp and Fuzzy Vertices Using α-Cuts." Advances in Fuzzy Systems 2019 (May 2, 2019): 1–11. http://dx.doi.org/10.1155/2019/5213020.

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Coloring of fuzzy graphs has many real life applications in combinatorial optimization problems like traffic light system, exam scheduling, register allocation, etc. In this paper, the concept of fuzzy chromatic polynomial of fuzzy graph is introduced and defined based on α-cuts of fuzzy graph. Two different types of fuzziness to fuzzy graph are considered in the paper. The first type was fuzzy graph with crisp vertex set and fuzzy edge set and the second type was fuzzy graph with fuzzy vertex set and fuzzy edge set. Depending on this, the fuzzy chromatic polynomials for some fuzzy graphs are discussed. Some interesting remarks on fuzzy chromatic polynomial of fuzzy graphs have been derived. Further, some results related to the concept are proved. Lastly, fuzzy chromatic polynomials for complete fuzzy graphs and fuzzy cycles are studied and some results are obtained.
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4

Chaitanya, Ch, and T. V. Pradeep Kumar. "ON THE COMPLETE PRODUCT OF FUZZY GRAPHS." South East Asian J. of Mathematics and Mathematical Sciences 18, no. 02 (September 24, 2022): 185–96. http://dx.doi.org/10.56827/seajmms.2022.1802.17.

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Strong fuzzy graph and complete fuzzy graph are two special kinds of fuzzy graphs in which each edge membership value equals the least of its vertex membership values incidental to the edge. In this research study, we obtain some interesting results on the complete product of a pair of strong fuzzy graphs as well as the complete product of a pair of complete fuzzy graphs. In precise, we prove that the complete product of two strong fuzzy graphs is again a strong fuzzy graph and the complete product of two complete fuzzy graphs is again a complete fuzzy graph. Also, we discuss the conditions under which the property of regularity will be mutually transmitted between the complete product of two fuzzy graphs and one of its factor fuzzy graphs
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5

Akram, Muhammad, and Neha Waseem. "Certain Metrics in m-Polar Fuzzy Graphs." New Mathematics and Natural Computation 12, no. 02 (June 8, 2016): 135–55. http://dx.doi.org/10.1142/s1793005716500101.

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In this paper, we present certain metrics in m-polar fuzzy graphs including antipodal m-polar fuzzy graphs and self median m-polar fuzzy graph of given m-polar fuzzy graphs. We illustrate the concepts of metric in m-polar fuzzy graphs by several examples and investigate some of their properties. We discuss some properties of isomorphic m-polar fuzzy graphs. We also describe an application of m-polar fuzzy graph in a road network.
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6

Havare, Özge Çolakoğlu, and Hamza Menken. "On Corona Product of Two Fuzzy Graphs." International Journal of Fuzzy Mathematical Archive 11, no. 02 (2016): 95–100. http://dx.doi.org/10.22457/ijfma.v11n2a5.

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Corona product of two fuzzy graphs which is analogous to the concept corona product operation in crisp graph theory is defined. The degree of an edge in corona product of fuzzy graphs is obtained. Also, the degree of an edge in fuzzy graph formed by this operation in terms of the degree of edges in the given fuzzy graphs in some particular cases is found. Moreover, it is proved that corona product of two fuzzy graphs is effective when two fuzzy graphs is effective fuzzy graphs.
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7

Repalle, V. N. Srinivasa Rao, and Fekadu Tesgera Agama. "2-Quasitotal Fuzzy Graphs and Their Total Coloring." Advances in Fuzzy Systems 2020 (November 20, 2020): 1–10. http://dx.doi.org/10.1155/2020/8814220.

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Coloring of fuzzy graphs has many real-life applications in combinatorial optimization problems like traffic light system, exam scheduling, and register allocation. The coloring of total fuzzy graphs and its applications are well studied. This manuscript discusses the description of 2-quasitotal graph for fuzzy graphs. The proposed concept of 2-quasitotal fuzzy graph is explicated by several numerical examples. Moreover, some theorems related to the properties of 2-quasitotal fuzzy graphs are stated and proved. The results of these theorems are compared with the results obtained from total fuzzy graphs and 1-quasitotal fuzzy graphs. Furthermore, it defines 2-quasitotal coloring of fuzzy total graphs and which is justified.
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8

Alshehri, Noura, and Muhammad Akram. "Intuitionistic Fuzzy Planar Graphs." Discrete Dynamics in Nature and Society 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/397823.

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Graph theory has numerous applications in modern sciences and technology. Atanassov introduced the concept of intuitionistic fuzzy sets as a generalization of fuzzy sets. Intuitionistic fuzzy set has shown advantages in handling vagueness and uncertainty compared to fuzzy set. In this paper, we apply the concept of intuitionistic fuzzy sets to multigraphs, planar graphs, and dual graphs. We introduce the notions of intuitionistic fuzzy multigraphs, intuitionistic fuzzy planar graphs, and intuitionistic fuzzy dual graphs and investigate some of their interesting properties. We also study isomorphism between intuitionistic fuzzy planar graphs.
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9

Mordeson, John N., and Sunil Mathew. "Fuzzy End Nodes in Fuzzy Incidence Graphs." New Mathematics and Natural Computation 13, no. 01 (January 31, 2017): 13–20. http://dx.doi.org/10.1142/s1793005717500028.

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The notion of a fuzzy end node in fuzzy incidence graphs is developed in this article. The concept of a fuzzy incidence graph is new and should be very useful in applications in fuzzy graphs and fuzzy networks. Relationships between weak incidence pairs and fuzzy incidence end nodes and fuzzy incidence cut vertices are developed.
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10

Broumi, Said, Florentin Smarandache, Mohamed Talea, and Assia Bakali. "An Introduction to Bipolar Single Valued Neutrosophic Graph Theory." Applied Mechanics and Materials 841 (June 2016): 184–91. http://dx.doi.org/10.4028/www.scientific.net/amm.841.184.

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In this paper, we first define the concept of bipolar single neutrosophic graphs as the generalization of bipolar fuzzy graphs, N-graphs, intuitionistic fuzzy graph, single valued neutrosophic graphs and bipolar intuitionistic fuzzy graphs.
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11

Khan, Waheed Ahmad, Babir Ali, and Abdelghani Taouti. "Bipolar Picture Fuzzy Graphs with Application." Symmetry 13, no. 8 (August 4, 2021): 1427. http://dx.doi.org/10.3390/sym13081427.

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In this manuscript, we introduce and discuss the term bipolar picture fuzzy graphs along with some of its fundamental characteristics and applications. We also initiate the concepts of complete bipolar picture fuzzy graphs and strong bipolar picture fuzzy graphs. Firstly, we apply different types of operations to bipolar picture fuzzy graphs and then we introduce various products of bipolar picture fuzzy graphs. Several other terms such as order and size, path, neighbourhood degrees, busy values of vertices and edges of bipolar picture fuzzy graphs are also discussed. These terminologies also lay the foundations for the discussion about the regular bipolar picture fuzzy graphs. Moreover, we also discuss isomorphisms, weak and co-weak isomorphisms and automorphisms of bipolar picture fuzzy graphs. Finally, at the base of bipolar picture fuzzy graph we present the construction of a bipolar picture fuzzy acquaintanceship graph, which would be an important tool to measure the symmetry or asymmetry of acquaintanceship levels of social networks, computer networks etc.
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12

K, Ameenal Bibi, and Devi M. "FUZZY ANTI-MAGIC LABELING ON SOME GRAPHS." Kongunadu Research Journal 5, no. 1 (June 30, 2018): 8–14. http://dx.doi.org/10.26524/krj244.

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In this Paper, we introduced the concept of fuzzy anti-magic labeling in graphs. We defined Fuzzy Anti-Magic Labeling (FAML) for Cycle, Star, Path and Antiprism graphs.A fuzzy graph G:(σ,μ)s known as fuzzy anti-magic graph if there exists two bijective functions σ : V->[0,1] and μ :V*V ->[0,1] such that μ u,v<σ(u)^σ(v) with the property that the sum of the edge labels incident to each vertex, the sums will all be different. We investigated and verified that fuzzy Cycle graphs, fuzzy Star graphs, fuzzy Path graphs and fuzzy antiprism graphs admits fuzzy anti-magic labeling.Further some properties related to fuzzy bridge and fuzzy cut vertex have been discussed.
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13

Mathew, Sunil, Hai Long Yang, and Jill K. Mathew. "Saturation in Fuzzy Graphs." New Mathematics and Natural Computation 14, no. 01 (March 2018): 113–28. http://dx.doi.org/10.1142/s1793005718500084.

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Edges of a fuzzy graph are mainly classified into [Formula: see text], [Formula: see text] and [Formula: see text]. In this paper, we study certain saturation counts with respect to the classification of edges. Characterizations for fuzzy cycles, fuzzy trees, blocks in fuzzy graphs and complete fuzzy graphs are also obtained using saturation counts.
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14

Yin, Songyi, Hongxu Li, and Yang Yang. "Product Operations on q-Rung Orthopair Fuzzy Graphs." Symmetry 11, no. 4 (April 23, 2019): 588. http://dx.doi.org/10.3390/sym11040588.

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The q-rung orthopair fuzzy graph is an extension of intuitionistic fuzzy graph and Pythagorean fuzzy graph. In this paper, the degree and total degree of a vertex in q-rung orthopair fuzzy graphs are firstly defined. Then, some product operations on q-rung orthopair fuzzy graphs, including direct product, Cartesian product, semi-strong product, strong product, and lexicographic product, are defined. Furthermore, some theorems about the degree and total degree under these product operations are put forward and elaborated with several examples. In particular, these theorems improve the similar results in single-valued neutrosophic graphs and Pythagorean fuzzy graphs.
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15

Sebastian, Arya, John N. Mordeson, and Sunil Mathew. "Generalized Fuzzy Graph Connectivity Parameters with Application to Human Trafficking." Mathematics 8, no. 3 (March 16, 2020): 424. http://dx.doi.org/10.3390/math8030424.

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Graph models are fundamental in network theory. But normalization of weights are necessary to deal with large size networks like internet. Most of the research works available in the literature have been restricted to an algorithmic perspective alone. Not much have been studied theoretically on connectivity of normalized networks. Fuzzy graph theory answers to most of the problems in this area. Although the concept of connectivity in fuzzy graphs has been widely studied, one cannot find proper generalizations of connectivity parameters of unweighted graphs. Generalizations for some of the existing vertex and edge connectivity parameters in graphs are attempted in this article. New parameters are compared with the old ones and generalized values are calculated for some of the major classes like cycles and trees in fuzzy graphs. The existence of super fuzzy graphs with higher connectivity values are established for both old and new parameters. The new edge connectivity values for some wider classes of fuzzy graphs are also obtained. The generalizations bring substantial improvements in fuzzy graph clustering techniques and allow a smooth theoretical alignment. Apart from these, a new class of fuzzy graphs called generalized t-connected fuzzy graphs are studied. An algorithm for clustering the vertices of a fuzzy graph and an application related to human trafficking are also proposed.
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16

Akram, Muhammad, Wieslaw A. Dudek, and M. Murtaza Yousaf. "Regularity in Vague Intersection Graphs and Vague Line Graphs." Abstract and Applied Analysis 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/525389.

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Fuzzy graph theory is commonly used in computer science applications, particularly in database theory, data mining, neural networks, expert systems, cluster analysis, control theory, and image capturing. A vague graph is a generalized structure of a fuzzy graph that gives more precision, flexibility, and compatibility to a system when compared with systems that are designed using fuzzy graphs. In this paper, we introduce the notion of vague line graphs, and certain types of vague line graphs and present some of their properties. We also discuss an example application of vague digraphs.
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17

.Deebamonica, A., and A. Marydayana. "TOTAL CHROMATIC NUMBER OF FUZZY BISTAR GRAPH & FUZZY HELM GRAPH." INTERNATIONAL JOURNAL OF MATHEMATICS AND COMPUTER RESEARCH 10, no. 12 (December 26, 2022): 3057–59. http://dx.doi.org/10.47191/ijmcr/v10i12.09.

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Fuzzy total chromatic number is the least value of k such that k-fuzzy total coloring exist. In this paper, we discussed the concept of total coloring of graphs to Fuzzy bistar graph and Fuzzy helm graph. Here we define fuzzy chromatic number of the fuzzy Bistar graph and Fuzzy Helm graph.
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18

Das, Sankar, Ganesh Ghorai, and Madhumangal Pal. "Picture fuzzy tolerance graphs with application." Complex & Intelligent Systems 8, no. 1 (September 30, 2021): 541–54. http://dx.doi.org/10.1007/s40747-021-00540-5.

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AbstractIn this study, the notions of picture fuzzy tolerance graphs, picture fuzzy interval containment graphs and picture fuzzy $$\phi $$ ϕ -tolerance graphs are established. Three special types of picture fuzzy tolerance graphs having bounded representations are introduced and studied corresponding properties of them taking $$\phi $$ ϕ as max, min and sum functions. Also, picture fuzzy proper and unit tolerance graphs are established and some related results are investigated. The class of picture fuzzy $$\phi $$ ϕ -tolerance chaingraphs which is the picture fuzzy $$\phi $$ ϕ -tolerance graphs of a nested family of picture fuzzy intervals are presented. A real-life application in sports competition is modeled using picture fuzzy min-tolerance graph. Also a comparison is given between picture fuzzy tolerance graphs and intuitionistic fuzzy tolerance graphs.
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19

Manjusha, O. T. "Set Domination in Fuzzy Graphs Using Strong Arcs." Pan-American Journal of Mathematics 1 (August 3, 2022): 9. http://dx.doi.org/10.28919/cpr-pajm/1-9.

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Set domination in fuzzy graphs is very useful for solving traffic problems during communication in computer networks and travelling networks. In this article, the concept of set domination in fuzzy graphs using strong arcs is introduced. The strong set domination number of complete fuzzy graph and complete bipartite fuzzy graph is determined. It is obtained the properties of the new parameter and related it to some other known domination parameters of fuzzy graphs. An upper bound for the strong set domination number of fuzzy graphs is also obtained.
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20

Deva, N., and A. Felix. "Designing DEMATEL method under bipolar fuzzy environment." Journal of Intelligent & Fuzzy Systems 41, no. 6 (December 16, 2021): 7257–73. http://dx.doi.org/10.3233/jifs-211112.

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Bipolar fuzzy graph is more precise than a fuzzy graph when dealing with imprecision as it is focusing on the positive and negative information of each vertex and edge. Nowadays, researchers have utilized bipolar fuzzy graphs in decision-making problems. Bipolar fuzzy competition graphs aid to compute the competition between the vertices in bipolar fuzzy graphs. To depict the best competitions among the competitions of bipolar fuzzy graphs, the best bipolar fuzzy competition graph can be defined using bipolar fuzzy α-cut and the strength of the competition between the vertices can also be determined. Fuzzy graphs are used well to frame modelling in real-time problems. In particular, when the real-time scenario is modelled using the bipolar fuzzy graph, it gives more precision and flexibility. At present, researchers have focused on decision-making techniques with bipolar fuzzy graphs. The DEMATEL method is one of the powerful decision-making tools. It effectively analyses the complicated digraphs and matrices. The fuzzy DEMATEL technique can convert the interrelations between factors into an intelligible structural model of the system and divide them into cause and effect groups. Therefore, this study attempts to design the DEMATEL method under the bipolar fuzzy environment. To illustrate this proposed technique, the problem of identifying the best mobile network is taken. With this method, the benefits and drawbacks of networks are measured and a complicated bipolar fuzzy directed graph can be transformed into a viewed structure.
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21

Zihni, Onur, Yıldıray Çelik, and Güven Kara. "Interval-Valued Fuzzy Soft Graphs." Topological Algebra and its Applications 5, no. 1 (December 20, 2017): 19–27. http://dx.doi.org/10.1515/taa-2017-0004.

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Abstract In this paper, we combine concepts of interval-valued fuzzy soft sets and graph theory. Then we introduce notations of interval-valued fuzzy soft graphs and complete interval-valued fuzzy soft graphs. We also present several different types operations including cartesian product, strong product and composition on interval-valued fuzzy soft graphs and investigate some properties of them.
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22

Gong, Zengtai, and Junhu Wang. "Hesitant fuzzy graphs, hesitant fuzzy hypergraphs and fuzzy graph decisions1." Journal of Intelligent & Fuzzy Systems 40, no. 1 (January 4, 2021): 865–75. http://dx.doi.org/10.3233/jifs-201016.

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Up to now, there have been a lot of research results about multi-attribute decision making problems by fuzzy graph theory. However, there are few investigations about multi-attribute decision making problems under the background of indecisiveness. The main reason is that the difference of cognition and the complexity of thinking by decision makers, for the same question have different opinions. In this paper, we proposed a hesitant fuzzy hypergraph model based on hesitant fuzzy sets and fuzzy hypergraphs. At the same time, some basic graph operations of hesitant fuzzy hypergraphs are investigated and several equivalence relationship between hesitant fuzzy hypergraphs, hesitant fuzzy formal concept analysis and hesitant fuzzy information systems are discussed. Since granular computing can deal with multi-attribute decision-making problems well, we considered the hesitant fuzzy hypergraph model of granular computing, and established an algorithm of multi-attribute decision-making problem based on hesitant fuzzy hypergraph model. Finally an example is given to illustrate the effectiveness of the algorithm.
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23

Talebi, A. A., G. Muhiuddin, S. H. Sadati, and Hossein Rashmanlou. "New concepts of domination in fuzzy graph structures with application." Journal of Intelligent & Fuzzy Systems 42, no. 4 (March 4, 2022): 3705–18. http://dx.doi.org/10.3233/jifs-211923.

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Fuzzy graphs have a prominent place in the mathematical modelling of the problems due to the simplicity of representing the relationships between topics. Gradually, with the development of science and in encountering with complex problems and the existence of multiple relationships between variables, the need to consider fuzzy graphs with multiple relationships was felt. With the introduction of the graph structures, there was better flexibility than the graph in dealing with problems. By combining a graph structure with a fuzzy graph, a fuzzy graph structure was introduced that increased the decision-making power of complex problems based on uncertainties. The previous definitions restrictions in fuzzy graphs have made us present new definitions in the fuzzy graph structure. The domination of fuzzy graphs has many applications in other sciences including computer science, intelligent systems, psychology, and medical sciences. Hence, in this paper, first we study the dominating set in a fuzzy graph structure from the perspective of the domination number of its fuzzy relationships. Likewise, we determine the domination in terms of neighborhood, degree, and capacity of vertices with some examples. Finally, applications of domination are introduced in fuzzy graph structure.
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24

Al-Masarwah, Anas, and Majdoleen Abu Qamar. "Certain Types of Fuzzy Soft Graphs." New Mathematics and Natural Computation 14, no. 02 (June 3, 2018): 145–56. http://dx.doi.org/10.1142/s1793005718500102.

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In this paper, we introduce the concepts of uniform vertex fuzzy soft graphs, uniform edge fuzzy soft graphs, degree of a vertex, total degree of a vertex and complement fuzzy soft graphs with some examples. Also, we study regular and totally regular fuzzy soft graphs, and the conditions under which the complement of regular fuzzy soft graph becomes regular as well as totally regular are discussed. Also, we obtain some results related to regular, totally regular and complete fuzzy soft graphs.
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25

Borzooei, R. A., B. Sheikh Hoseini, and M. Mohseni Takallo. "Results on t-Fuzzy Graphs." New Mathematics and Natural Computation 16, no. 01 (March 2020): 143–61. http://dx.doi.org/10.1142/s179300572050009x.

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It is much more practical to use the [Formula: see text]-norm than the minimum in defining the fuzzy graph. Hence, the concept of [Formula: see text]-fuzzy graph was introduced by Mordeson et al. in [J. N. Mordeson and S. Mathew, [Formula: see text]-norm Fuzzy Graphs, New Mathematics and Natural Computation 14(1) (2018) 129–143]. In this paper, we concentrate on the relatively new concept of fuzzy adjacency matrix of that [Formula: see text]-fuzzy graphs. The purpose of this paper is to further develop a product of this fuzzy adjacency matrix based on [Formula: see text]-fuzzy graphs. Moreover, two kinds of Boolean matrix are defined and relation between Normal Boolean matrix, product of adjacency matrix and 1-level cut Boolean matrix is obtained.
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26

Kalaiarasi, Kalaichelvan, L. Mahalakshmi, Nasreen Kausar, Sajida Kousar, and Parameshwari Kattel. "Perfect Fuzzy Soft Tripartite Graphs and Their Complements." Discrete Dynamics in Nature and Society 2022 (May 25, 2022): 1–10. http://dx.doi.org/10.1155/2022/1108887.

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Fuzzy soft graphs are efficient numerical tools for simulating the uncertainty of the real world. A fuzzy soft graph is a perfect fusion of the fuzzy soft set and the graph model that is widely used in a variety of fields. This paper discusses a few unique notions of perfect fuzzy soft tripartite graphs (PFSTG), as well as the concepts of complement of perfect fuzzy soft tripartite graphs (CPFSTGs). Because soft sets are most useful in real-world applications, the newly developed concepts of perfect soft tripartite fuzzy graphs will lead to many theoretical applications by adding extra fuzziness in analysing. We look at some of their properties and come up with a few results that are related to these concepts. Furthermore, we investigated some fundamental theorems and illustrated an application of size of perfect fuzzy soft tripartite graphs in employee selection for an institution using the perfect fuzzy soft tripartite graph.
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27

V, Jesudas Selvaraj, and Ponnappan C Y. "Perfect Matching in Various Fuzzy Graphs." ECS Transactions 107, no. 1 (April 24, 2022): 19237–51. http://dx.doi.org/10.1149/10701.19237ecst.

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An induced fuzzy sub graph <H> of a fuzzy graph G (V,E) is said to be a matching if every vertex of G (V,E) is incident with at most a vertex in <H>. A induced fuzzy sub graph <H> of a fuzzy graph G (V,E) is said to be a perfect matching if every vertex of G (V,E) is incident with exactly a vertex in <H>. In this paper we will define a perfect matching in fuzzy graphs. Further we investigate the bounds and properties of matching numbers in various fuzzy graphs.
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28

Çelik, Yildiray. "On bipolar fuzzy soft graphs." Creative Mathematics and Informatics 27, no. 2 (2018): 123–32. http://dx.doi.org/10.37193/cmi.2018.02.04.

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In this paper, we combine the concepts of bipolar fuzzy soft sets and graph theory. Then we introduce notations of bipolar fuzzy soft graph and strong bipolar fuzzy soft graph. We also present several different types of operations including cartesian product, strong product and composition on bipolar fuzzy soft graphs and investigate some properties of them.
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29

Noppakaew, Passawan, Kaewkan Hengthonglert, and Sawanya Sakuntasathien. "Dominating Broadcasts in Fuzzy Graphs." Mathematics 10, no. 2 (January 17, 2022): 281. http://dx.doi.org/10.3390/math10020281.

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Broadcasting problems in graph theory play a significant role in solving many complicated physical problems. However, in real life there are many vague situations that sometimes cannot be modeled using usual graphs. Consequently, the concept of a fuzzy graph GF:(V,σ,μ) has been introduced to deal with such problems. In this study, we are interested in defining the notion of dominating broadcasts in fuzzy graphs. We also show that, in a connected fuzzy graph containing more than one element in σ*, a dominating broadcast always exists, where σ* is {v∈V|σ(v)>0}. In addition, we investigate the relationship between broadcast domination numbers, radii, and domination numbers in a fuzzy graph as follows; γb(GF)≤min{r(GF),γ(GF)}, where γb(GF) is the broadcast domination number, r(GF) is the radius, and γ(GF) is domination numbers in fuzzy graph GF, with |σ*|>1.
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30

Hanif, Muhammad Zeeshan, Naveed Yaqoob, Muhammad Riaz, and Muhammad Aslam. "Linear Diophantine fuzzy graphs with new decision-making approach." AIMS Mathematics 7, no. 8 (2022): 14532–56. http://dx.doi.org/10.3934/math.2022801.

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<abstract><p>The concept of linear Diophantine fuzzy set (LDFS) is a new mathematical tool for optimization, soft computing, and decision analysis. The aim of this article is to extend the notion of graph theory towards LDFSs. We initiate the idea of linear Diophantine fuzzy graph (LDF-graph) as a generalization of certain theoretical concepts including, q-rung orthopair fuzzy graph, Pythagorean fuzzy graph, and intuitionistic fuzzy graph. We extend certain properties of crisp graph theory towards LDF-graph including, composition, join, and union of LDF-graphs. We elucidate these operations with various illustrations. We analyze some interesting results that the composition of two LDF-graphs is a LDF-graph, cartesian product of two LDF-graphs is a LDF-graph, and the join of two LDF-graphs is a LDF-graph. We describe the idea of homomorphisms for LDF-graphs. We observe the equivalence relation via an isomorphism between LDF-graphs. Some significant results related to complement of LDF-graph are also investigated. Lastly, an algorithm based on LDFSs and LDF-relations is proposed for decision-making problems. A numerical example of medical diagnosis application is presented based on proposed approach.</p></abstract>
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31

Islam, Sk Rabiul, and Madhumangal Pal. "Hyper-Wiener index for fuzzy graph and its application in share market." Journal of Intelligent & Fuzzy Systems 41, no. 1 (August 11, 2021): 2073–83. http://dx.doi.org/10.3233/jifs-210736.

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Topological indices have an important role in molecular chemistry, network theory, spectral graph theory and several physical worlds. Most of the topological indices are defined in a crisp graph. As fuzzy graphs are more generalization of crisp graphs, those indices have more application in fuzzy graphs also. In this article, we introduced the fuzzy hyper-Wiener index (FHWI) and studied this index for various fuzzy graphs like path, cycle, star, etc and provided some interesting bounds of FHWI for that fuzzy graph. A lower bound of FHWI is established for n-vertex connected fuzzy graph depending on strength of a strong edges. A relation between FHWI of a tree and its maximum spanning tree is established and this index is calculated for the saturated cycle. Also, at the end of the article, an application in the share market of this index is presented.
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32

Al Mutab, Huda Mutab. "Fuzzy Graphs." JOURNAL OF ADVANCES IN MATHEMATICS 17 (October 3, 2019): 232–47. http://dx.doi.org/10.24297/jam.v17i0.8443.

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In this paper, neighbourly irregular fuzzy graphs, neighbourly total irregular fuzzy graphs, highly irregular fuzzy graphs and highly total irregular fuzzy graphs are introduced. A necessary and sufficient condition under which neighbourly irregular and highly irregular fuzzy graphs are equivalent is provided. We define d2 degree of a vertex in fuzzy graphs and total d2 -degree of a vertex in fuzzy graphs and (2, k)-regular fuzzy graphs, totally (2, k)- regular fuzzy graphs are introduced. (2, k)- regular fuzzy graphs and totally (2, k)-regular fuzzy graphs are compared through various examples.
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33

Jiang, Huiqin, and Yongsheng Rao. "Connectivity Index in Vague Graphs with Application in Construction." Discrete Dynamics in Nature and Society 2022 (February 15, 2022): 1–15. http://dx.doi.org/10.1155/2022/9082693.

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The vague graph (VG), which has recently gained a place in the family of fuzzy graph (FG), has shown good capabilities in the face of problems that cannot be expressed by fuzzy graphs and interval-valued fuzzy graphs. Connectivity index (CI) in graphs is a fundamental issue in fuzzy graph theory that has wide applications in the real world. The previous definitions’ limitations in the connectivity of fuzzy graphs directed us to offer new classifications in vague graph. Hence, in this paper, we investigate connectivity index, average connectivity index, and Randic index in vague graphs with several examples. Also, one of the motives of this research is to introduce some special types of vertices such as vague connectivity enhancing vertex, vague connectivity reducing vertex, and vague connectivity neutral vertex with their properties. Finally, an application of connectivity index in the selected town for building hospital is presented.
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34

Chen, Dong Li, and Yan Zhang. "Nonstandard Characterization of Fuzzy Graphs." Applied Mechanics and Materials 411-414 (September 2013): 1392–95. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.1392.

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Based on general procedure for the construction of nonstandard graphs, we first construct a nonstandard fuzzy graph. Subsequently, we define the nonstandard hull of a fuzzy graph, and discuss its properties.
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35

Nagoor Gani, A., Muhammad Akram, and D. Rajalaxmi (a) Subahashini. "Novel Properties of Fuzzy Labeling Graphs." Journal of Mathematics 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/375135.

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The concepts of fuzzy labeling and fuzzy magic labeling graph are introduced. Fuzzy magic labeling for some graphs like path, cycle, and star graph is defined. It is proved that every fuzzy magic graph is a fuzzy labeling graph, but the converse is not true. We have shown that the removal of a fuzzy bridge from a fuzzy magic cycle with odd nodes reduces the strength of a fuzzy magic cycle. Some properties related to fuzzy bridge and fuzzy cut node have also been discussed.
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36

Alzoubi, Wael Ahmad, and As’ad Mahmoud As’ad Alnaser. "A Study on Connectivity Concepts in Intuitionistic Fuzzy Graphs." WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL 16 (January 15, 2021): 77–82. http://dx.doi.org/10.37394/23203.2021.16.5.

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In this paper, we introduced some concepts of connectivity in an intuitionistic fuzzy graphs, also we study intuitionistic fuzzy cut vertices and intuitionistic fuzzy bridges in fuzzy graph. Connectivity in complete intuitionistic fuzzy graphs is also studied
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37

Mathew, Sunil, and John N. Mordeson. "Fuzzy Influence Graphs." New Mathematics and Natural Computation 13, no. 03 (September 28, 2017): 311–25. http://dx.doi.org/10.1142/s1793005717400129.

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Trafficking in persons is the most heinous and condemnable organized crime of our time. The eradication of this crime must involve the full cooperation of all. In this paper, we provide a mathematical method to model such cooperation. We use a new concept in fuzzy graph theory, namely, that of incidence. We introduce fuzzy influence graph and characterize influence cutpairs in fuzzy influence graphs since their removal increases the number of connected components of a fuzzy network and thus weakens the potential flow in the network. Some of the properties of influence pairs and influence cutnodes are also studied.
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38

R, Shanmugapriya, and Mary Jiny D. "Fuzzy Super Resolving Number of Fuzzy Labelling Graphs." Journal of Advanced Research in Dynamical and Control Systems 11, no. 0009-SPECIAL ISSUE (September 25, 2019): 606–11. http://dx.doi.org/10.5373/jardcs/v11/20192612.

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39

SEN, M. K., G. CHOWDHURY, and D. S. MALIK. "FUZZY INTERSECTION GRAPHS OF FUZZY SEMIGROUPS." New Mathematics and Natural Computation 02, no. 01 (March 2006): 1–10. http://dx.doi.org/10.1142/s179300570600035x.

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Let S be a semigroup. This paper studies the intersection graphs of fuzzy semigroups. It is shown that the fuzzy intersection graph Int(G(S)), of S, is complete if and only if S is power joined. If Γ(S) denotes the set of all fuzzy right ideals of S, then the fuzzy intersection graph Int(Γ(S)) is complete if and only if S is fuzzy right uniform. Moreover, it is shown that Int(Γ(S)) is chordal if and only if for a,b,c,d ∈ S, some pair from {a,b,c,d} has a right common multiple property. It is also shown that if Int(G(S)) is complete and S has the acc on subsemigroups, then S is cyclic.
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40

Akram, Muhammad, Jawaria Dar, and Adeel Farooq. "Planar Graphs under Pythagorean Fuzzy Environment." Mathematics 6, no. 12 (November 25, 2018): 278. http://dx.doi.org/10.3390/math6120278.

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Graph theory plays a substantial role in structuring and designing many problems. A number of structural designs with crossings can be found in real world scenarios. To model the vagueness and uncertainty in graphical network problems, many extensions of graph theoretical ideas are introduced. To deal with such uncertain situations, the present paper proposes the concept of Pythagorean fuzzy multigraphs and Pythagorean fuzzy planar graphs with some of their eminent characteristics by investigating Pythagorean fuzzy planarity value with strong, weak and considerable edges. A close association is developed between Pythagorean fuzzy planar and dual graphs. This paper also includes a brief discussion on non-planar Pythagorean fuzzy graphs and explores the concepts of isomorphism, weak isomorphism and co-weak isomorphism for Pythagorean fuzzy planar graphs. Moreover, it presents a problem that shows applicability of the proposed concept.
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41

Karunambigai, M. G., Muhammad Akram, S. Sivasankar, and K. Palanivel. "Clustering Algorithm for Intuitionistic Fuzzy Graphs." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 25, no. 03 (May 22, 2017): 367–83. http://dx.doi.org/10.1142/s0218488517500155.

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In this paper, we present certain algorithms for clustering the vertices of fuzzy graphs(FGs) and intuitionistic fuzzy graphs(IFGs). These algorithms are based on the edge density of the given graph. We apply the algorithms to practical problems to derive the most prominent cluster among them. We also introduce parameters for intuitionistic fuzzy graphs.
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42

Shiono, Yasunori, Tadaaki Kirishima, Yoshinori Ueda, and Kensei Tsuchida. "Drawing Algorithm for Fuzzy Graphs Using the Partition Tree." Journal of Advanced Computational Intelligence and Intelligent Informatics 16, no. 5 (July 20, 2012): 641–52. http://dx.doi.org/10.20965/jaciii.2012.p0641.

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Fuzzy graphs have been used frequently and effectively as a method for sociogram analysis. A fuzzy graph has the fundamental characteristic of being able to express a variety of relationships between nodes. The drawing of fuzzy graphs has been studied in computer-aided analysis systems with human interfaces and methods using genetic algorithms. However, computer-aided analysis systems with human interfaces do not provide for automatic drawing, while methods using genetic algorithms have the defect of requiring too much execution time for finding a locally optimum solution. To overcome these defects, we propose an algorithm for drawing intelligible and comprehensive fuzzy graphs using a partition tree. This method automatically draws the fuzzy graphwith nodes arranged on the intersections of a latticed space. Since nodes are optimally arranged on the latticed intersections and put together at a nearby position in accordance with the transition of clusters according to cluster levels in the partition tree, drawing the algorithm makes fuzzy relations easier to understand through fuzzy graph representation. Moreover, fuzzy graphs can be drawn faster than by conventional methods. This paper describes the algorithm and its verification by introducing a system implementing the method for displaying fuzzy graphs. Moreover, we have carried out a case study in which a questionnaire has been administered to students, allowing us to analyze human relations quantitatively using a method based on fuzzy theory. Human relations are represented as fuzzy graphs by our algorithm and analyzed using the fuzzy graph.
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43

Dhanyamol, M. V., and Sunil Mathew. "On Certain Transit Functions in Fuzzy Graphs." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 25, no. 06 (November 17, 2017): 917–28. http://dx.doi.org/10.1142/s0218488517500398.

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Gates in fuzzy graphs are introduced in this paper. Gates of a graph are vertices which satisfy certain conditions. Gatedness in a graph is a property of its induced subgraphs (or a subsets of the vertex set), which depends on the metric defined on it. Gates can be considered as a generalization of cutvertices in fuzzy graphs. Strong gates are gates corresponding to g-distance. We examine certain relations between cutvertices and fuzzy cutvertices. Also, some geodetic properties of strong gates in fuzzy graphs are discussed.
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44

Alzubaidi, A. M., and M. Dammak. "GRAPHIC TOPOLOGY ON FUZZY GRAPHS." Advances in Mathematics: Scientific Journal 11, no. 10 (October 14, 2022): 853–68. http://dx.doi.org/10.37418/amsj.11.10.4.

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In this paper, we study the graphic topology $\mathcal{T}_{G}$ for a fuzzy graph. We give some properties of this topology, in particular we prove that $\mathcal{T}_{G}$ is an Alexandroff topology and when two graphs are isomorphic, their graphic topologies will be homeomorphic. We give some properties matching graphs and homeomorphic topology spaces. Finally, we investigate the connectedness of this topology and some relations between the connectedness of the graph and the topology $\mathcal{T}_{G}$.
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45

Koam, Ali N. A., Muhammad Akram, and Peide Liu. "Decision-Making Analysis Based on Fuzzy Graph Structures." Mathematical Problems in Engineering 2020 (August 12, 2020): 1–30. http://dx.doi.org/10.1155/2020/6846257.

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A graph structure is a useful framework to solve the combinatorial problems in various fields of computational intelligence systems and computer science. In this research article, the concept of fuzzy sets is applied to the graph structure to define certain notions of fuzzy graph structures. Fuzzy graph structures can be very useful in the study of various structures, including fuzzy graphs, signed graphs, and the graphs having labeled or colored edges. The notions of the fuzzy graph structure, lexicographic-max product, and degree and total degree of a vertex in the lexicographic-max product are introduced. Further, the proposed concepts are explained through several numerical examples. In particular, applications of the fuzzy graph structures in decision-making process, regarding detection of marine crimes and detection of the road crimes, are presented. Finally, the general procedure of these applications is described by an algorithm.
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46

Harinath, Purnima, and S. Lavanya. "FUZZY GRAPH STRUCTURE OF FLOWER GRAPHS." Far East Journal of Applied Mathematics 96, no. 4 (June 8, 2017): 213–20. http://dx.doi.org/10.17654/am096040213.

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47

K.Kalaiarasi and R.Divya. "Fuzzy Colouring of Interval-Valued Fuzzy Graph." International Journal of Fuzzy Mathematical Archive 14, no. 01 (2017): 47–57. http://dx.doi.org/10.22457/ijfma.v14n1a7.

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Fuzzy graphs have revolutionized the analysis of problematic data to arrive at a better decision making power are different kinds. Among them, the interval-valued fuzzy graph in the simplest and generalized once. The main purpose of this paper is to introduce the chromatic number of an interval-valued fuzzy graph. Here working rule of an interval-valued fuzzy graph, power cut graph are discussed.
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48

Seethalakshmi, R., and R. B. Gnanajothi. "Strong Regular L-Fuzzy Graphs." International Journal of Trend in Scientific Research and Development Volume-1, Issue-5 (August 31, 2017): 503–9. http://dx.doi.org/10.31142/ijtsrd2333.

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49

Jiang, Huiqin, Ali Asghar Talebi, Zehui Shao, Seyed Hossein Sadati, and Hossein Rashmanlou. "New Concepts of Vertex Covering in Cubic Graphs with Its Applications." Mathematics 10, no. 3 (January 19, 2022): 307. http://dx.doi.org/10.3390/math10030307.

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Graphs serve as one of the main tools for the mathematical modeling of various human problems. Fuzzy graphs have the ability to solve uncertain and ambiguous problems. The cubic graph, which has recently gained a position in the fuzzy graph family, has shown good capabilities when faced with problems that cannot be expressed by fuzzy graphs and interval-valued fuzzy graphs. Simultaneous application of fuzzy and interval-valued fuzzy membership indicates a high flexibility in modeling uncertainty issues. The vertex cover is a fundamental issue in graph theory that has wide application in the real world. The previous definition limitations in the vertex covering of fuzzy graphs has directed us to offer new classifications in terms of cubic graph. In this study, we introduced the strong vertex covering and independent vertex covering in a cubic graph with strong edges and described some of its properties. One of the motives of this research was to examine the changes in the strong vertex covering number of a cubic graph if one vertex is omitted. This issue can play a decisive role in covering the graph vertices. Since many of the problems ahead are of hybrid type, by reviewing some operations on the cubic graph we were able to determine the strong vertex covering number on the most important cubic product operations. Finally, two applications of strong vertex covering and strong vertex independence are presented.
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50

K.S, Kanzul Fathima, and Jahir Hussain R. "An Introduction to Fuzzy Edge Coloring." JOURNAL OF ADVANCES IN MATHEMATICS 11, no. 10 (January 28, 2016): 5742–48. http://dx.doi.org/10.24297/jam.v11i10.801.

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In this paper, a new concept of fuzzy edge coloring is introduced. The fuzzy edge coloring is an assignment of colors to edges of a fuzzy graph G. It is proper if no two strong adjacent edges of G will receive the same color. Fuzzy edge chromatic number of G is least positive integer for which G has a proper fuzzy edge coloring. In this paper, the fuzzy edge chromatic number of different classes of fuzzy graphs and the fuzzy edge chromatic number of fuzzy line graphs are found. Isochromatic fuzzy graph is also defined.
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