Abstract
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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