engleski

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

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 factor (RS) and optimization of thin layer chromatographic separation of model solutions containing seven compounds. Very good correlation was achieved between predicted and calculated RS data, and low absolute and relative errors were obtained.

Thin layer chromatography ; Optimization ; Artificial neural networks ; Genetic algorithms

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