Prediction of equilibrium constants in aqueous solution. I. The extrapolation of equilibrium constants to zero ionic strength using PLS, artificial neural networks, and genetic "soft" modelling

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Authors	FARKOVÁ Marta LUBAL Přemysl HAVEL Josef
Year of publication	2004
Type	Article in Periodical
Magazine / Source	Chemical Papers
MU Faculty or unit	Faculty of Science
Citation
Field	Analytic chemistry
Keywords	Debye-Hückel equation; equilibrium constants; artificial neural networks; genetic algorithm; partial least-squares
Description	Extrapolation of formation constants to zero ionic strength using "soft" modelling with partial least-squares, genetic algorithm, and artificial neural networks (ANN) methods was examined and results of individual approaches were compared. The methods allow a rapid and sufficiently accurate prediction of thermodynamic formation constants, ion-size parameters, and salting-out coefficients from experimental equilibrium data, among them the ANN method was found most reliable.
Related projects:	Artificial neural networks and experimental design in analytical chemistry, especially in separation methods