Artificial neural network prediction of retention factors of some benzene derivatives and heterocyclic compounds in micellar electrokinetic chromatography

Electrophoresis

Volumn 26, Issue 18, 2005, Pages 3438-3444

  Golmohammadi, Hassan ^a   Fatemi, Mohammed H ^a  

^a UNIVERSITY OF MAZANDARAN   (Iran)

Author keywords

Artificial neural network; Micellar electrokinetic chromatography; Multiple linear regression; Quantitative structure property relationship; Retention factors

Indexed keywords

BENZENE; ELECTRODYNAMICS; MOLECULES; NEURAL NETWORKS;

BENZENE DERIVATIVES; DESCRIPTORS; HETEROCYCLIC COMPOUND; MICELLAR ELECTROKINETIC CHROMATOGRAPHY; MULTIPLE LINEAR REGRESSIONS; NEURAL NETWORK PREDICTIONS; QUANTITATIVE STRUCTURE PROPERTY RELATIONSHIPS; RETENTION FACTORS; SELECTION TECHNIQUES; VARIABLES SELECTIONS;

MULTIPLE LINEAR REGRESSION;

BENZENE DERIVATIVE; HETEROCYCLIC COMPOUND;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CHEMICAL ANALYSIS; COMPUTER SIMULATION; LINEAR REGRESSION ANALYSIS; MICELLAR ELECTROKINETIC CHROMATOGRAPHY; MOLECULAR WEIGHT; POLARIZATION; PREDICTION; QUANTITATIVE STRUCTURE PROPERTY RELATION; STATISTICAL MODEL; VALIDATION PROCESS;

EID: 26244446816     PISSN: 01730835     EISSN: None     Source Type: Journal    
DOI: 10.1002/elps.200500203     Document Type: Article

References (31)

1. Terabe, S., Otsuka, K., Ishikawa, K., Tsuchiyo, A., Ando, T., Anal. Chem. 1984, 56, 111-113.
2. Jandera, P., Fischer, J., Jebava, J., Effenberger, H., J. Chromatogr. A 2001, 914, 233-244.
3. Beale, S. C., Anal. Chem. 1998, 70, R279-R300.
4. Kuhn, R., Hoffstetter-Kuhn, S., Capillary Electrophoresis - Principle and Practice, Springer-Verlag, New York 1972.
5. Fu, X., Lu, J., Capillary Electrophoresis, Zhejiang University Press, Hangzhou, China 1997.
6. Kuo, C. H., Sun, S. W., Anal. Chim. Acta 2003, 482, 47-58.
7. Garcia-March, F. J., Anton-Fos, G. M., Prez-Gimenez, F., Salaberti-Salvador, M. T., Cresel-del-Pozo, R. A., de Juliano-Ortiz, J. V., J. Chromatogr. A 1996, 719, 45-51.
8. Woloszyn, T. F., Jurs, P. C., Anal. Chem. 1992, 64, 3059-3063.
9. Kaliszan, R., Kaliszan, A., Noctor, T. G. A., J. Chromatogr. 1992, 609, 69-81.
10. Jalali-Heravi, M., Shen, Y., Hassanisadi, M., Khaledi, M. G., Electrophoresis 2005, 26, 1874-1885.
11. Detroyer, A., Heyden, V., Cambre, I., Massart, D. L., J. Chromatogr. A 2003, 986, 227-238.
12. Vegas, J. M., Zufiria, P. J., Neural Networks 2004, 17, 233-245.
13. Schweitzer, R. C., Morris, J. B., Anal. Chim. Acta 1999, 384, 285-303.
14. Tong, C. S., Cheng, K. C., Chemom. Intell. Lab. Syst. 1999, 49, 135-150.
15. Palenzuela, B., Simonet, B. M., Garcia, R. M., Rois, A., Valcarcel, M., Anal. Chem. 2004, 76, 3012-3017.
16. Kašička, V., Electrophoresis 2003, 24, 4013-4046.
17. Fatemi, M. H., J. Chromatogr. A 2002, 955, 273-280.
18. Fatemi, M. H., J. Chromatogr. A 2003, 1002, 221-229.
19. Fatemi, M. H., J. Chromatogr. A 2004, 1038, 231-237.
20. Fatemi, M. H., Jalali-Heravi, M., Konuze, E., Anal. Chim. Acta 2003, 486, 101-108.
21. Fuguet, E., Rafols, C., Bosch, E., Abraham, M. H., Roses, M., J. Chromatogr. A 2002, 942, 237-248.
22. Whalden, E. K., Jurs, P. C., Anal. Chem. 1981, 53, 2184-2187.
23. Stouch, T. R., Jurs, P. C., J. Chem. Inf. Comput. Sci. 1986, 26, 4-12.
24. MOPAC Package, Version 6, US Air Force Academy, Colorado Springs, CO, USA.
25. Hertz, J., Krogh, A., Palmer, R., Introduction to the Theory of Neural Computation, Addison-Wesley, Redwood City, CA, USA 1991.
26. Ripley, B. D., Pattern Recognition and Neural Networks, Cambridge University Press, Cambridge 1996.
27. Haykin, S., Neural Networks, A Comprehensive Foundation, Macmillan, New York 1993.
28. Wasserman, P. D., Advanced Methods in Neural Computing, Van Nostrand Reinhold, New York 1993.
29. Zupan, J., Gasteiger, J., Neural Networks in Chemistry and Drug Design, VCH, Weinheim 1999.
30. Jalali-Heravi, M., Fatemi, M. H., Anal. Chim. Acta 2000, 415, 95-103.
31. Jalali-Heravi, M., Fatemi, M. H., J. Chromatogr. A 2000, 897, 227-235.