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The quantitative structure-property relationship (QSPR) was studied for the prediction of glass transition temperatures of polystyrenes on a set of 107 polystyrenes using artificial neural networks combined with genetic function approximation. Descriptors of the polymers were derived from their corresponding cyclic dimer structures. A nonlinear model with four descriptors was developed with squared...
The quantitative structure-property relationship approach was performed to study the relative fluorescence intensity ratio (R) of Eu(DBM)3Phen (DBM—dibenzoylmethane, Phen—1,10-phenanthroline) in 34 different solvents. The multilinear regression analysis and artificial neural networks were employed to develop linear and nonlinear models, respectively. The proposed linear model contains six descriptors,...
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