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  • 1 University of Zagreb Department of Fundamental Natural and Engineering Sciences, Faculty of Textile Technology Prilaz baruna Filipovića 28a 10000 Zagreb Croatia
  • 2 University of Zagreb Laboratory of Analytical Chemistry, Department of Applied Chemistry, Faculty of Textile Technology Prilaz baruna Filipovića 28a 10000 Zagreb Croatia
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A novel method is proposed for optimization of simultaneous thinlayer chromatographic separation of seven amino acids. For this purpose we used a useful combination of genetic algorithms (GA) with artificial neural networks (ANN). Methods investigated in this work were successfully used for prediction of resolution (RS) and optimization of the thin-layer chromatographic separation of model solutions containing the seven compound. Very good correlation was achieved between predicted and calculated RS data, and low absolute and relative errors were obtained.

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  • SJR Quartile Score (2019): Q3 Analytical Chemistry
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  • Impact Factor (2018): 0.826
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  • SJR Hirsch-Index (2018): 29
  • SJR Quartile Score (2018): Q3 Analytical Chemistry
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Publication Programme: 2020. Vol. 33.
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