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On analysis of silicon dioxide based on topological indices and entropy measure via regression model

dc.contributor.authorHuang, Rongbing
dc.date.accessioned2026-10-19T21:45:54Z
dc.date.issued2024-09-28
dc.description.abstractThe construction sector accounts for around 95% of the commercial usage of silicon dioxide (sand), for example, in the making of concrete. There are several uses for quartz, however in order to get a purer material, chemical processing is needed. Graph theory proved to be very beneficial for other research, especially in the applied sciences. In particular, graph theory has greatly influenced the field of chemistry. To do this, a transformation is needed to produce a graph with the vertices representing the atoms in the chemical compound and the edges indicating the bonds between the atoms. This graph then represents a chemical network or structure. In a graph, a vertex's valency (or degree) is determined by the number of edges that are incident to it. The entropy of a probability quantifies a system's level of uncertainty. In this article, we compute Zagreb-type indices and then compute the entropy measure. In order to evaluate the relevance of each kind, this article builds several edge degree-based entropies that link to the indices and establish how to adjust them. We also create the logarithmic regression model between indices and entropy.
dc.identifier.citationHuang, R., Hanif, M. F., Siddiqui, M. K., Hanif, M. F., & Gegbe, B. (2024). On analysis of silicon dioxide based on topological indices and entropy measure via regression model. Scientific Reports, 14(1), 22478. https://doi.org/10.1038/s41598-024-73163-8
dc.identifier.doi10.1038/s41598-024-73163-8
dc.identifier.urihttps://doi.org/10.1038/s41598-024-73163-8
dc.identifier.urihttps://dspace.njala.edu.sl/handle/20.500.144402/907
dc.language.isoen
dc.publisherNature Portfolio
dc.relation.ispartofScientific Reports
dc.rightsCC BY-NC-ND
dc.subjectTopological Indices
dc.titleOn analysis of silicon dioxide based on topological indices and entropy measure via regression model
dc.typeArticle

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