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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
Farková, M., Lubal, P. and Havel, J. 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 Chemical Papers, Vol.58, No. 5, 2004, 299-305
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Document type:
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Článok z časopisu / Journal Article |
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Collection:
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Chemical papers
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| Attached Files |
| Name |
Description |
MIMEType |
Size |
Downloads |
n585a299.pdf
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585a299.pdf |
application/pdf |
321.19KB |
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| Author(s) |
Farková, M.
Lubal, P.
Havel, J.
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| Title |
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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| Journal name |
Chemical Papers
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| Publication date |
2004
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| Year available |
2004
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| Volume number |
58
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| Issue number |
5
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| ISSN |
0366-6352
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| Start page |
299
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| End page |
305
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| Place of publication |
Poland
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| Publisher |
Versita
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| Collection year |
2004
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| Language |
english
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| Subject |
250000 Chemical Sciences
250400 Analytical Chemistry
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| Abstract/Summary |
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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