Bipolar fuzzy graphs based on the product operator

From both theoretical and experimental perspectives, bipolar fuzzy set theory serves as a foundation for bipolar cognitive modeling and multi-agent decision analysis, where the product operator may be preferred over the min operator in some scenarios. In this paper, we discuss the basic properties of operations on product bipolar fuzzy graphs (PBFGs)(bipolar fuzzy graphs based on the product operator) such as direct product, Cartesian product, strong product, lexicographic product, union, ring sum and join. Also we define the notion of complement of PBFGs and investigate its properties. Moreover, application of PBFG theory is presented in multi-agent decision making.Publisher's Versio

On bipolar complex intuitionistic fuzzy graphs

In the present article, we devised the novel approach on the bipolar complex intuitionistic fuzzy set, bipolar complex intuitionistic fuzzy graphs and operations namely composition, cartesian product, join and union of the bipolar complex intuitionistic fuzzy graphs are elucidated with certain examples. Finally, the notions of isomorphisms and complement of bipolar complex intuitionistic fuzzy graphs are established and reviewed many of its characteristics.Publisher's Versio

Generalized Interval Valued Neutrosophic Graphs of First Type

In this paper, motivated by the notion of generalized single valued neutrosophic graphs of first type, we defined a new neutrosophic graphs named generalized interval valued neutrosophic graphs of first type (GIVNG1) and presented a matrix representation for it and studied few properties of this new concept. The concept of GIVNG1 is an extension of generalized fuzzy graphs (GFG1) and generalized single valued neutrosophic of first type (GSVNG1)

On some operations and density of m-polar fuzzy graphs

AbstractThe theoretical concepts of graphs are highly utilized by computer science applications, social sciences, and medical sciences, especially in computer science for applications such as data mining, image segmentation, clustering, image capturing, and networking. Fuzzy graphs, bipolar fuzzy graphs and the recently developed m-polar fuzzy graphs are growing research topics because they are generalizations of graphs (crisp). In this paper, three new operations, i.e., direct product, semi-strong product and strong product, are defined on m-polar fuzzy graphs. It is proved that any of the products of m-polar fuzzy graphs are again an m-polar fuzzy graph. Sufficient conditions are established for each to be strong, and it is proved that the strong product of two complete m-polar fuzzy graphs is complete. If any of the products of two m-polar fuzzy graphs G1 and G2 are strong, then at least G1 or G2 must be strong. Moreover, the density of an m-polar fuzzy graph is defined, the notion of balanced m-polar fuzzy graph is studied, and necessary and sufficient conditions for the preceding products of two m-polar fuzzy balanced graphs to be balanced are established. Finally, the concept of product m-polar fuzzy graph is introduced, and it is shown that every product m-polar fuzzy graph is an m-polar fuzzy graph. Some operations, like union, direct product, and ring sum are defined to construct new product m-polar fuzzy graphs

Certain Operations on Bipolar Fuzzy Graph Structures

A graph structure is a useful tool in solving the combinatorial problems in different areas of computer science and computational intelligence systems. A bipolar fuzzy graph structure is a generalization of a bipolar fuzzy graph. In this paper, we present several different types of operations, including composition, Cartesian product, strong product, cross product, and lexicographic product on bipolar fuzzy graph structures. We also investigate some properties of operations

The hub number of a fuzzy graph

In this paper, we introduced the concepts of hub number in fuzzy graph and is denoted by h(G). The hub number of fuzzy graph G is the minimum fuzzy cardinality among all minimal fuzzy hub sets . We determine the hub number h(G) for several classes of fuzzy graph and obtain Nordhaus-Gaddum type results for this parameter. Further, some bounds of h(G) are investigated. Also the relations between h(G) and other known parameters in fuzzy graphs are investigated.Publisher's Versio

Some properties of m-polar fuzzy graphs

AbstractIn many real world problems, data sometimes comes from n agents (n ≥ 2), i.e., “multipolar information” exists. This information cannot be well-represented by means of fuzzy graphs or bipolar fuzzy graphs. Therefore, m-polar fuzzy set theory is applied to graphs to describe the relationships among several individuals. In this paper, some operations are defined to formulate these graphs. Some properties of strong m-polar fuzzy graphs, self-complementary m-polar fuzzy graphs and self-complementary strong m-polar fuzzy graphs are discussed

Some properties of vague graph structures

A graph structure is a generalization of simple graphs. Graph structures are very useful tools for the study of different domains of computational intelligence and computer science. A vague graph structure is a generalization of a vague graph. In this research paper, we present several different types of operations including cartesian product, cross product, lexicographic product, union, and composition on vague graph structures. We also introduce some results of operations.Publisher's Versio