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On comparative analysis of a two dimensional star gold structure via regression models
Muhammad Farhan Hanif1, Hasan Mahmood2, Shahbaz Ahmad1
1Abdus Salam School of Mathematical Sciences, Government College University, Lahore, Pakistan.
This study analyzes star gold structures with beta graphene, calculating topological indices and entropy. It reveals relationships between these measures using regression models to understand network dynamics.
Area of Science:
- Materials Science
- Network Science
- Computational Chemistry
Background:
- Topological indices are crucial for understanding network connectivity and complexity.
- Entropy measures provide insights into information richness and unpredictability within networks.
- Star gold structures with beta graphene present unique characteristics for network analysis.
Purpose of the Study:
- To compute degree-based topological indices for star gold structures with beta graphene.
- To calculate entropy measures for quantifying uncertainty and information in these networks.
- To explore and model the relationships between topological descriptors and entropy.
Main Methods:
- Computation of various degree-based topological indices.
- Calculation of entropy measures for network characterization.
- Application of logarithmic, linear, and quadratic regression models to analyze descriptor-entropy relationships.
Main Results:
- Quantified topological indices and entropy for star gold-beta graphene structures.
- Established correlations between topological indices and entropy using regression analysis.
- Identified patterns governing network behavior through merged regression models.
Conclusions:
- The study elucidates the intricate connection between topological indices and entropy in star gold structures.
- Findings enhance the understanding of star gold structure dynamics.
- A visual framework is provided for interpreting the behavior of these complex networks.
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