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On physical analysis of topological indices and entropy measures for porphyrazine structure using logarithmic regression model

Authors: Asma Khalid; Shoaib Iqbal; Muhammad Kamran Siddiqui; Tariq Javed Zia; Brima Gegbe;

On physical analysis of topological indices and entropy measures for porphyrazine structure using logarithmic regression model

Abstract

The porphyrazine structure, known for its high chemical and thermal stability, has become a significant focus in materials science, chemical reactivity, functionalization, and drug design. By utilizing the new Zagreb-type indices to analyze the chemical structure of porphyrazine, we can gather more information about their bonding and connecting patterns. This enables us to construct an entropy measure that helps evaluate the stability of the material and predict its behavior in different scenarios. Furthermore, establishing correlations between these indices and entropy using logarithmic regression models allows for a deeper understanding of complex properties of porphyrazine. This, in turn, opens up new possibilities for the compound's potential applications across various scientific and technical fields. In our work, we have used the M-polynomial to derive molecular descriptors for degree-based topological indices and determine the entropy of the porphyrazine structure based on these descriptors.

Keywords

Porphyrazine structure, Topological indices, Science, Q, R, Logarithmic regression, Medicine, Graph entropy, M-polynomial, Regression analysis, Article

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
Green
hybrid