Artificial neural networks other regression methods

Methods other than thermodynamic cycles are often used to calculate acid dissociation constants. Previous publications implement the theoretical relationship between pKa and structural property [6], bond valence methods and bond lengths [33], pKa correlations with highest occupied molecular orbital (HOMO) energies and frontier molecular orbitals [34], and artificial neural networks [35] to predict pKa values. In addition much work has been done using physical properties as quantitative structure-activity relationship (QSAR) descriptors, and regression equations with such descriptors to yield accurate pKa values for specific classes of molecules [36-47]. The correlation of pKas to various molecular properties, however, is often restricted to specific classes of compounds, and it is... 

Finally, Chapter 6 goes into two new regression paradigms artificial neural networks and support vector machines. Quite different from the other regression methods presented in the book, they are gaining acceptance because they can handle non-linear systems and/or noisy data. This step forward is introduced briefly and, once more, a review is presented with practical applications in the atomic spectroscopy field. Not surprisingly, most papers deal with complex measurements [e.g. non-linear calibration or... 

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