Isometry on Interval-valued Fuzzy Graphs

TL;DR

This paper explores the concept of isometry within interval-valued fuzzy graphs, which are more adaptable than traditional fuzzy graphs, enhancing applications in data mining, image segmentation, and networking.

Contribution

It introduces the notion of isometry specifically for interval-valued fuzzy graphs, expanding the theoretical framework of fuzzy graph analysis.

Findings

Defines isometry for interval-valued fuzzy graphs

Establishes properties and conditions for isometry in this context

Provides potential applications in computer science fields

Abstract

Especially in research areas of computer science such as data mining, image segmentation, clustering image capturing and networking. The interval-valued fuzzy graphs are more flexible and compatible than fuzzy graphs due to the fact that they allowed the degree of membership of a vertex to an edge to be represented by interval valued in [0,1] rather than the crisp real values between 0 and 1.