Degree-Based Entropy of Some Classes of Networks

S. Nagarajan, Muhammad Imran, P. Mahesh Kumar, K. Pattabiraman, Muhammad Usman Ghani

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

A topological index is a number that is connected to a chemical composition in order to correlate a substance’s chemical makeup with different physical characteristics, chemical reactivity, or biological activity. It is common to model drugs and other chemical substances as different forms, trees, and graphs. Certain physico-chemical features of chemical substances correlate better with degree-based topological invariants. Predictions concerning the dynamics of the continuing pandemic may be made with the use of the graphic theoretical approaches given here. In Networks, the degree entropy of the epidemic and related trees was computed. It highlights the essay’s originality while also implying that this piece has improved upon prior literature-based realizations. In this paper, we study an important degree-based invariant known as the inverse sum indeg invariant for a variety of graphs of biological interest networks, including the corona product of some interesting classes of graphs and the pandemic tree network, curtain tree network, and Cayley tree network. We also examine the inverse sum indeg invariant features for the molecular graphs that represent the molecules in the bicyclic chemical graphs.

Original languageEnglish
Article number960
JournalMathematics
Volume11
Issue number4
DOIs
Publication statusPublished - Feb 2023

Keywords

  • chemical graph theory
  • mathematical chemistry
  • networks
  • topological invariants

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • General Mathematics
  • Engineering (miscellaneous)

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