Exploring Entropy Measures with Topological Indices on Subdivided Cage Networks via Linear Regression Analysis - Rongbing Huang; Muhammad Farhan Hanif; Muhammad Faisal Hanif; Muhammad Kamran Siddiqui; Mazhar Hussain; Eihab Bashier (Applied Artificial Intelligence)
In this study, we investigate entropy measurements for subdivided cage networks based on topological indices. We specifically calculate different entropy, redefining Zagreb entropy, [Formula: see text],[Formula: see text], [Formula: see text] entropy, atom bond connection entropy, and Randic entropy. We examine the graphical behavior of various entropy measures using the line fit approach. The results highlight patterns in the distribution of entropy values and interactions between them, which shed light on the intricate connectivity and structural properties of segmented cage networks. This work improves our understanding of cage network dynamics and provides a visual framework for interpreting their behavior.