Publication details
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
| Authors | |
|---|---|
| Year of publication | 2004 |
| Type | Article in Periodical |
| Magazine / Source | Chemical Papers |
| MU Faculty or unit | |
| 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. |
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