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Degree-Based Entropy of Some Classes of Networks

Author

Listed:
  • S. Nagarajan

    (Department of Mathematics, Kongu Arts and Science College (Autonomous), Erode 638107, India)

  • Muhammad Imran

    (Department of Mathematical Sciences, College of Science, United Arab Emirates University, Al Ain 15551, United Arab Emirates)

  • P. Mahesh Kumar

    (Department of Mathematics, Kongu Arts and Science College (Autonomous), Erode 638107, India)

  • K. Pattabiraman

    (Department of Mathematics, Government Arts College (Autonomous), Kumbakonam 612002, India)

  • Muhammad Usman Ghani

    (Institute of Mathematics, Khawaja Fareed University of Engineering & Information Technology, Abu Dhabi Road, Rahim Yar Khan 64200, Pakistan)

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.

Suggested Citation

  • S. Nagarajan & Muhammad Imran & P. Mahesh Kumar & K. Pattabiraman & Muhammad Usman Ghani, 2023. "Degree-Based Entropy of Some Classes of Networks," Mathematics, MDPI, vol. 11(4), pages 1-14, February.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:4:p:960-:d:1067186
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    References listed on IDEAS

    as
    1. Md. Ashraful Alam & Muhammad Usman Ghani & Muhammad Kamran & Muhammad Shazib Hameed & Riaz Hussain Khan & A. Q. Baig & Hassan Raza, 2022. "Degree-Based Entropy for a Non-Kekulean Benzenoid Graph," Journal of Mathematics, Hindawi, vol. 2022, pages 1-12, June.
    2. Muhammad Usman Ghani & Muhammad Kashif Maqbool & Reny George & Austine Efut Ofem & Murat Cancan, 2022. "Entropies Via Various Molecular Descriptors of Layer Structure of H 3 BO 3," Mathematics, MDPI, vol. 10(24), pages 1-13, December.
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    1. Muhammad Usman Ghani & Muhammad Kashif Maqbool & Reny George & Austine Efut Ofem & Murat Cancan, 2022. "Entropies Via Various Molecular Descriptors of Layer Structure of H 3 BO 3," Mathematics, MDPI, vol. 10(24), pages 1-13, December.

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