Open Access

ARTICLE

Vertex-Edge Degree Based Indices of Honey Comb Derived Network

by Muhammad Ibrahim^1,*, Sadia Husain², Nida Zahra¹, Ali Ahmad²

1 Centre for Advanced Studies in Pure and Applied Mathematics, Bahauddin Zakariya University, Multan, Pakistan
2 College of Computer Sciences and Information Technology, Jazan University, Jazan, Saudi Arabia

* Corresponding Author: Muhammad Ibrahim. Email:

Computer Systems Science and Engineering 2022, 40(1), 247-258. https://doi.org/10.32604/csse.2022.018227

Received 01 March 2021; Accepted 29 April 2021; Issue published 26 August 2021

Abstract

Chemical graph theory is a branch of mathematics which combines graph theory and chemistry. Chemical reaction network theory is a territory of applied mathematics that endeavors to display the conduct of genuine compound frameworks. It pulled the research community due to its applications in theoretical and organic chemistry since 1960. Additionally, it also increases the interest the mathematicians due to the interesting mathematical structures and problems are involved. The structure of an interconnection network can be represented by a graph. In the network, vertices represent the processor nodes and edges represent the links between the processor nodes. Graph invariants play a vital feature in graph theory and distinguish the structural properties of graphs and networks. In this paper, we determined the newly introduced topological indices namely, first -degree Zagreb index, first -degree Zagreb index, second -degree Zagreb index, -degree Randic index, -degree atom-bond connectivity index, -degree geometric-arithmetic index, -degree harmonic index and -degree sum-connectivity index for honey comb derived network. In the analysis of the quantitative structure property relationships (QSPRs) and the quantitative structureactivity relationships (QSARs), graph invariants are important tools to approximate and predicate the properties of the biological and chemical compounds. Also, we give the numerical and graphical representation of our outcomes.

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