Summary
An Artificial Neural Network (ANN) was investigated as a method to model retention times of anions in nonsuppressed and suppressed ion chromatography (IC) using a range of eluents and stationary phases, with the results being compared to those obtained using mathematical retention models. The optimal ANN architecture was determined for six specific IC cases of increasing complexity. Analysis of the retention times predicted using the ANN and those predicted by the mathematical models showed that the ANN approach yielded superior performance in all of the above cases. The use of a limited training data set configured in a central composite experimental design was suitable for application of the ANN to non-suppressed IC but was not applicable to suppressed IC, for which a more extensive training data set was necessary.
Similar content being viewed by others
References
P. R. Haddad, P. E. Jackson, Ion Chromatography-Principles and Applications, Journal of Chromatography Library, Vol. 46, Elsevier, Amsterdam, 1990, Ch. 6, p. 165.
J. E. Madden, P. R. Haddad, P. Hajós, Trends Anal. Chem.15, 531 (1996).
A. D. Sosimenko, P. R. Haddad, J. Chromatogr.546, 37 (1991).
J. E. Madden, P. R. Haddad, J. Chromatogr. A,829, 65 (1998).
J. E. Madden, P. R. Haddad, J. Chromatogr. A accepted for publication.
J. E. Madden, P. R. Haddad, J. Chromatogr. A accepted for publication.
J. Zupan, J. Gasteiger, Anal. Chem. Acta248, 1 (1991).
M. Bos, H. T. Weber, Anal. Chim. Acta,247, 97 (1991).
B. J. Wythoff, S. P. Levine, S. A. Tomellini, Anal. Chem.62, 2702 (1990).
M. Bos, A. Bos, W. E. van der Linden, Anal. Chim. Acta233, 31 (1990).
S. Ventura, M. Silva, D. Pérez-Bendito, Anal. Chem.67, 4458 (1995).
M. Blanco, J. Coello, H. Iturriaga, S. Maspoch, M. Redón, Anal. Chem.67, 4477 (1995).
J. Havel, E. M. Peña, A. Rojas-Hernández, J.-P. Doucet, A. Panaye, J. Chromatogr. A793, 317 (1998).
M. Farková, E. M. Peña, J. Havel, J. Chromatogr. A (1998). in print (accepted).
V. Dohnal, J. Havel, in “Combination of Experimental Designs and Artificial Neural Networks”, 10th International Symposium on Chiral Discrimination, 30-8-1998 to 3-9-1998, Vienna, Austria, p. 112.
P. M. J. Coenegracht, H. J. Metting, E. M. van Loo, G. J. Snoeijer, D. A. Doornbos, J. Chromatogr.631, 145 (1993).
H. J. Metting, P. M. J. Coenegracht, J. Chromatogr. A728, 47 (1996).
Y. Hu, G. Zhou, J. Kang, Y. Du, J. Huang, J. Ge, J. Chromatogr. A734, 259 (1996).
H. Miao, M. Yu, S. Hu, J. Chromatogr. A749, 5 (1996).
E. Marengo, M. C. Gennaro, S. Angelino, J. Chromatogr. A799, 47 (1998).
G. Sacchero, M. C. Bruzzoniti, C. Sarzanini, E. Mentasti, H. J. Metting, P. M. J. Coenergracht, J. Chromatogr. A799, 35 (1998).
P. Hajós, O. Horváth, V. Denke, Anal. Chem.67, 434 (1995).
J. L. McCelland, D. E. Rumelhart, in “Explorations in Parallel Distributed Processing,” The MIT Press, Massachusetts, (1988).
A. Panaye, J. P. Doucet, B. T. Fan, E. Feuilleabois, P. Ladd, Chem. Intell. Lab. Sys.24, 129 (1994).
M. T. Spining, J. A. Darsey, B. G. Sumpter, D. W. Noid, J. Chem. Educ.71, 406 (1994).
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Havel, J., Madden, J.E. & Haddad, P.R. Prediction of retention times for anions in ion chromatography using Artificial Neural Networks. Chromatographia 49, 481–488 (1999). https://doi.org/10.1007/BF02467746
Received:
Revised:
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/BF02467746