A Computer-Based Method to Determine Predictive Potential of Distance-Spectral Descriptors for Measuring the π-Electronic Energy of Benzenoid Hydrocarbons With Applications

Graph signal processing deals with signals whose domain, defined by a graph, is irregular. The total π-electron energy or simply the π-electronic energy, as calculated within Hückel tight-binding molecular orbital approximation, one of important quantum-theoretical characteristic conjugated molecules. In this paper, we propose an efficient computer-assisted computational method to determine eigenvalues-based distance descriptors for chemical compounds which are then used learn quantitative relationship between activity/property and structure (QSAR/QSPR) compound. Comparisons other similar methods show that our proposed possesses less algorithmic complexities more computationally diverse. predictive potential measuring benzenoid hydrocarbons. Importantly, three new matrices and, unexpectedly, results spectral based on outperform all well-known in literature. Specifically, second atom-bond connectivity Estrada index best correlation coefficient 0.9997. Applications certain infinite families carbon nanotubes nanocones presented. obtained can potentially be these theoretically higher accuracy negligible error.