Year: 2025
Type: article
Abstract: Networks are commonly represented as graphs, where vertices denote entities and edges capture relationships based on shared attributes. Granulation of a network is important for the structural analysis and understanding of its underlying patterns. In this paper, we introduce a distance-based granular computing framework for analyzing networks modeled by intersection graphs. We define these networks as information systems and investigate their granular structures using a distance-based representation. Based on the concepts of indiscernibility between two vertices using the distance from a set, we study indiscernibility partitions on the vertex set. Using the concept of discernibility between vertices, we define the distance-based discernibility matrix and explore its properties. We identify all minimal resolving sets using the discernibility matrix. Furthermore, using the proposed method, we study a transportation network for urban traffic planning.
Source: AIMS Mathematics
DOI: 10.3934/math.2025479
Institutions: Jazan University, Bahauddin Zakariya University
Language: English
Topic: Rough Sets and Fuzzy Logic
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,200
Funder: Jazan University
OpenAlex ID: W4410249233