Use of artificial neural networks in capillary zone electrophoresis

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Authors	FARKOVÁ Marta PEŇA-MÉNDEZ Eladia María HAVEL Josef
Year of publication	1999
Type	Article in Periodical
Magazine / Source	J. Chromatogr. A.
MU Faculty or unit	Faculty of Science
Citation
Field	Analytic chemistry
Description	The use of Artificial Neural Networks (ANN) for non-linear modeling of symmetric and nonsymmetric peaks in Capillary Zone Electrophoresis (CZE) and in optimization of CZE methods was studied. It was shown that ANN can be used to estimate peak parameters and in combination with experimental design can be applied for efficient prediction of optimal separation conditions. The great advantage is that no use of the explicit model of the separation process and no knowledge of the physicochemical constants are needed.
Related projects:	Structure and character of bonding, properties and analysis of synthetic and natural molecular ensembles