Use of artificial neural networks in capillary zone electrophoresis

FARKOVÁ, Marta, Eladia María PEŇA-MÉNDEZ and Josef HAVEL. Use of artificial neural networks in capillary zone electrophoresis. J. Chromatogr. A. Amsterdam (The Netherlands): Elsevier Science, 1999, vol. 848, 1-2, p. 365-374. ISSN 0021-9606.

Basic information

• Original name: Use of artificial neural networks in capillary zone electrophoresis
• Authors: FARKOVÁ, Marta, Eladia María PEŇA-MÉNDEZ and Josef HAVEL.
• Edition: J. Chromatogr. A. Amsterdam (The Netherlands), Elsevier Science, 1999, 0021-9606.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 10406 Analytical chemistry
• Country of publisher: Netherlands
• Confidentiality degree: is not subject to a state or trade secret
• Impact factor: Impact factor: 3.289
• RIV identification code: RIV/00216224:14310/99:00002117
• Organization unit: Faculty of Science
• UT WoS: 000081413600033

Abstract

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.

Links

• MSM 143100011, plan (intention): Name: Struktura a vazebné poměry, vlastnosti a analýza syntetických a přírodních molekulových ansamblů

Investor: Ministry of Education, Youth and Sports of the CR, Structure and character of bonding, properties and analysis of synthetic and natural molecular ensembles