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A model developed to predict aqueous solubility at different temperatures has been proposed based on quantitative structure–property relationships (QSPR) methodology. The prediction consists of two steps. The first one predicts the value of k parameter in the linear equation
, where Sw is the value of solubility and T is the value of temperature. The second step uses Random Forest technique...
The development of a new quantitative structure–property relationship (QSPR) model to predict aqueous solubility (S w ) accurately for compounds of military interest is presented. The ability of the new model to predict solubility is assessed and compared to available experimental data. A large set of structurally diverse organic compounds was used in this analysis. SiRMS methodology was employed...
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