Use of fuzzy regression for calibration in thin-layer chromatography/densitometry

A new fuzzy regression algorithm was successfully applied to calibration in thin-layer chromatography (TLC)/densitometry. Different regression techniques were also considered, and objective quality coefficients were used for evaluation of the results. Depending on the structure of the data, the fuzzy procedure can improve the results dramatically. From the results reported in this paper and other unpublished results, it appears clear that the calibration procedure based on fuzzy regression is the most suitable regression method in quantitative TLC.