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The purpose of this paper is to present a novel way for developing quantitative structure-property relationship (QSPR) models to predict the gas-to-propanol solvation enthalpy (ΔHsolv) of 95 organic compounds. Different kinds of descriptors were calculated for each compound using the Dragon software package. The variable selection technique of replacement method (RM) was employed to select...
The main aim of the present work was development of a quantitative structure-property relationship (QSPR) method using an artificial neural network (ANN) for the prediction of inherent viscosity (η inh ) of a data set of 75 optically active polymers containing natural amino acids. The total of 540 descriptors was calculated for all molecules in the data set. In the next step an ANN was constructed...
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