Application of different training methodologies for the development of a back propagation artificial neural network retention model in ion chromatography-Reference-Cited by-同舟云学术

Application of different training methodologies for the development of a back propagation artificial neural network retention model in ion chromatography

Published:2008 Issue:2 Volume:22 Page:106-113
ISSN:0886-9383
Container-title:Journal of Chemometrics
language:en
Short-container-title:J. Chemometrics

Author:

Bolanča Tomislav,Cerjan-Stefanović Štefica,Ukić Šime,Rogošić Marko,Luša Melita

Publisher

Wiley

Subject

Applied Mathematics,Analytical Chemistry

Reference40 articles.

1. Quantitative Column Liquid Chromatography: A Survey of Chemometric Methods. Elsevier: Amsterdam, 1984.

2. Optimisation of Chromatographic Selectivity: A Guide to Method Development. Elsevier: Amsterdam, 1986.

3. Selectivity and Detectability Optimisation in HPLC. Wiley: New York, 1989.

4. The future of chromatography: optimizing the separation

5. (ed.). Retention and Selectivity in Liquid Chromatography. Elsevier: Amsterdam, 1995.

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