Abstract
We introduced a new concept called the Fuzzy square difference labeling. We proved that the path graph (Pn), the cycle graph (Cn), the star graph (Sn) and the complete bipartite graph (Km,n, n ≤ 3) are Fuzzy square difference graphs.
Highlights
Fuzzy graph theory has numerous applications in many domains including networking, data mining, image capturing, communication, clustering, planning and scheduling
Nagoor Gani [2][3], who studied the novel properties of fuzzy labeling graphs
He proved that many standard graphs like path, cycle, complete graph, wheels, comb, star, crown and some other graphs are square difference graphs
Summary
Fuzzy graph theory has numerous applications in many domains including networking, data mining, image capturing, communication, clustering, planning and scheduling. In comparison to fuzzy and classical models, fuzzy labeling models have more flexibility, precision and compatability to system. They have many applications in Chemistry, Physics, Computer Science and other branches of Mathematics. Fuzzy logic had been studied by Lukasiewicz and Tarski [4] It was Rosenfeld [5] who considered fuzzy relations on fuzzy sets and developed the theory of fuzzy graphs in 1975. He studied the concept of fuzzy trees, blocks, bridges and cut nodes in fuzzy graphs. The concept of Square difference labeling was introduced by J. He proved that many standard graphs like path, cycle, complete graph, wheels, comb, star, crown and some other graphs are square difference graphs
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
