On analysis of entropy measure via logarithmic regression model for 2D-honeycomb networks

Caicai Feng; Muhammad Farhan Hanif; Muhammad Kamran Siddiqui; Mazhar Hussain; Nazir Hussain

doi:10.1140/epjp/s13360-023-04547-4

On analysis of entropy measure via logarithmic regression model for 2D-honeycomb networks

Caicai Feng
, Muhammad Farhan Hanif
, Muhammad Kamran Siddiqui^*
, Mazhar Hussain
, Nazir Hussain

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

A well-known structure in materials science and nanotechnology, the 2D-Honeycomb network has unique topological features and prospective uses. In this study, we introduce and explore newly defined Zagreb indices designed exclusively for 2D-Honeycomb Networks as we dig into the world of complicated network research. We investigate the links between these indices and entropy measures through a thorough analysis, shedding insight into the complex interaction between structural features and information content. In addition, we use a logarithmic regression model to reveal the network’s underlying patterns. Our research advances knowledge of 2D-honeycomb networks and illustrates the utility of logarithmic regression in complex system modeling.

Original language	English
Article number	924
Journal	European Physical Journal Plus
Volume	138
Issue number	10
DOIs	https://doi.org/10.1140/epjp/s13360-023-04547-4
State	Published - Oct 2023
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature.

ASJC Scopus subject areas

General Physics and Astronomy
Fluid Flow and Transfer Processes

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10.1140/epjp/s13360-023-04547-4

Cite this

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title = "On analysis of entropy measure via logarithmic regression model for 2D-honeycomb networks",

abstract = "A well-known structure in materials science and nanotechnology, the 2D-Honeycomb network has unique topological features and prospective uses. In this study, we introduce and explore newly defined Zagreb indices designed exclusively for 2D-Honeycomb Networks as we dig into the world of complicated network research. We investigate the links between these indices and entropy measures through a thorough analysis, shedding insight into the complex interaction between structural features and information content. In addition, we use a logarithmic regression model to reveal the network{\textquoteright}s underlying patterns. Our research advances knowledge of 2D-honeycomb networks and illustrates the utility of logarithmic regression in complex system modeling.",

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AU - Feng, Caicai

AU - Hanif, Muhammad Farhan

AU - Siddiqui, Muhammad Kamran

AU - Hussain, Mazhar

AU - Hussain, Nazir

PY - 2023/10

Y1 - 2023/10

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AB - A well-known structure in materials science and nanotechnology, the 2D-Honeycomb network has unique topological features and prospective uses. In this study, we introduce and explore newly defined Zagreb indices designed exclusively for 2D-Honeycomb Networks as we dig into the world of complicated network research. We investigate the links between these indices and entropy measures through a thorough analysis, shedding insight into the complex interaction between structural features and information content. In addition, we use a logarithmic regression model to reveal the network’s underlying patterns. Our research advances knowledge of 2D-honeycomb networks and illustrates the utility of logarithmic regression in complex system modeling.

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JF - European Physical Journal Plus

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ER -

On analysis of entropy measure via logarithmic regression model for 2D-honeycomb networks

Abstract

Bibliographical note

ASJC Scopus subject areas

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Cite this