Neural Network−Topological Indices Approach to the Prediction of Properties of Alkene
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TL;DR
A topological indices vector of five parameters (χ, P, w, l, s) including three grades of structural information was set up as a molecular descriptor to predict the normal boiling point, the density, and the refractive index of alkenes with a neural network.
Abstract
A topological indices vector of five parameters (χ, P, w, l, s ) including three grades of structural information was set up as a molecular descriptor to predict the normal boiling point, the density, and the refractive index of alkenes with a neural network. The five parameters are the connection index χ, the polarity number p, w, l representing the effect of a double bond on the properties, and s distinguishing enantiomers of alkenes. The estimation results show average accuracies of 1.3% with maximum deviations of 16%.