Use of Genetic Algorithms and Artificial Neural Networks to Predict the Resolution of Amino Acids in Thin-Layer Chromatography

摘要

A novel method is proposed for optimization of simultaneous thin-layer 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 (Us) and optimization of the thin-layer chromatographic separation of model solutions containing the seven compound. Very good correlation was achieved between predicted and calculated R_S data, and low absolute and relative errors were obtained.