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Application of principal component-genetic algorithm-artificial neural network for prediction acidity constant of various nitrogen-containing compounds in water

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Abstract

Principal component-genetic algorithm-multiparameter linear regression (PC-GA-MLR) and principal component-genetic algorithm-artificial neural network (PC-GA-ANN) models were applied for prediction acidity constant (pK a ) for various nitrogen-containing compounds. A data set that consisted of 282 various compounds, including 55 anilines, 77 amines, 82 pyridines, 14 pyrimidines, 26 imidazoles and benzimidazoles, and 28 quinolines, is used in this work. A large number of theoretical descriptors were calculated for each compound. The first 179 principal components (PCs) were found to explain more than 99.9% of variances in the original data matrix. From the pool of these PCs, the genetic algorithm was employed for selection of the best set of extracted PCs for PC-MLR and PC-ANN models. The models were generated using 15 PCs as variables. For evaluation of the predictive power of the models, pK a values of 56 compounds in the prediction set were calculated. Root mean square errors (RMSE) for PC-GA-MLR and PC-GA-ANN models are 1.4863 and 0.0750. Comparison of the results obtained by the models reveals superiority of the PC-GA-ANN model relative to the PC-GA-MLR model. Mean percent deviation for the PC-GA-ANN model in the prediction set is 2.123. The improvements are due to the fact that pK a of the compounds demonstrates non-linear correlations with the PCs.

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Acknowledgments

The authors wish to acknowledge the vice-presidency of research, University of Mohaghegh Ardabili, for financial support of this work.

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Authors and Affiliations

  1. Department of Chemistry, Faculty of Science, University of Mohaghegh Ardabili, Ardabil, Iran

    Aziz Habibi-Yangjeh, Eslam Pourbasheer & Mohammad Danandeh-Jenagharad

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  1. Aziz Habibi-Yangjeh
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  2. Eslam Pourbasheer
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  3. Mohammad Danandeh-Jenagharad
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Correspondence to Eslam Pourbasheer.

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Habibi-Yangjeh, A., Pourbasheer, E. & Danandeh-Jenagharad, M. Application of principal component-genetic algorithm-artificial neural network for prediction acidity constant of various nitrogen-containing compounds in water. Monatsh Chem 140, 15–27 (2009). https://doi.org/10.1007/s00706-008-0049-7

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  • DOI: https://doi.org/10.1007/s00706-008-0049-7

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