https://doi.org/10.1140/epjp/s13360-023-03817-5
Regular Article
Implementing QSPR modeling via multiple linear regression analysis to operations research: a study toward nanotubes
1
School of Mathematics and Statistics, Pingdingshan University, 467000, Pingdingshan, China
2
Henan International Joint Laboratory for Multidimensional Topology and Carcinogenic Characteristics Analysis of Atmospheric Particulate Matter PM2.5, 467000, Pingdingshan, China
3
Department of Natural Sciences and Humanities, University of Engineering and Technology, 54000, Lahore(RCET), Pakistan
4
Department of Mathematics, Lahore College for Women University, Lahore, Pakistan
Received:
31
December
2022
Accepted:
15
February
2023
Published online:
3
March
2023
Chemical graph theory significantly predicts multifarious physio-chemical properties of complex and multidimensional compounds when investigated through topological descriptors and QSPR modeling. The targeted compounds are widely studied nanotubes attaining exquisite nanostructures due to their distinguishable properties attaining numeric values. The studied nanotubes are carbon, naphthalene, boron nitride, V-phenylene, and titania nanotubes. In this research work, these nanotubes are characterized through their significance level by implementing highly applicable MCDM techniques. TOPSIS, COPRAS, and VIKOR are used to perform a comparative analysis between them through each optimal ranking. The criteria originated from multiple linear regression modeling established between degree-based topological descriptors and the physio-chemical properties of each nanotube.
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