Modelling of Normal Boiling Points of Hydroxyl Compounds by Radial Basis Networks
Volume 4, Issue 2, April 2016, Pages: 24-29
Received: May 3, 2016;
Published: May 4, 2016
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Liangjie Jin, School of Chemical Engineering and Technology, Tianjin University, Tianjin, PR China
Peng Bai, School of Chemical Engineering and Technology, Tianjin University, Tianjin, PR China
Radial basis networks (RBN) were applied to link molecular descriptor and boiling points of 168 hydroxyl compounds. The total database was randomly divided into a training set(134), a validation set(17) and a testing set(17). Each compound in the lowest energy conformation was numerically characterized with E-dragon software. Then 8 molecular descriptors were selected to develop the RBN model. Simulated with the final optimum RBN model [8-35(64)-1], the root mean square errors (RMSE) for the training, the validation and the testing set were 5.55, 4.28, and 5.33, and the correlation coefficients R=0.994(training), 0.994(validation), 0.993(testing). The final RBN model was compared with the multiple linear regression approach and showed more satisfactory results.
Modelling of Normal Boiling Points of Hydroxyl Compounds by Radial Basis Networks, Modern Chemistry.
Vol. 4, No. 2,
2016, pp. 24-29.
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