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- W2330434512 endingPage "726" @default.
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- W2330434512 abstract "In this work, the artificial neural network−group contribution (ANN−GC) method has been applied to represent/predict the solubilities of pure chemical compounds in water over the (293 to 298) K temperature range at atmospheric pressure. A set of 3585 pure compounds from various chemical families has been investigated to propose a comprehensive and predictive method. The obtained results show a squared correlation coefficient (R2) value of 0.96 and a root-mean-square error of 0.4 for the calculated/predicted properties with respect to existing experimental values, demonstrating the reliability of the proposed model." @default.
- W2330434512 created "2016-06-24" @default.
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- W2330434512 date "2011-02-04" @default.
- W2330434512 modified "2023-09-25" @default.
- W2330434512 title "Representation/Prediction of Solubilities of Pure Compounds in Water Using Artificial Neural Network−Group Contribution Method" @default.
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- W2330434512 doi "https://doi.org/10.1021/je101061t" @default.
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