TY - JOUR
T1 - Artificial neural networks as a multivariate calibration tool
T2 - modelling the Fe-Cr-Ni system in X-ray fluorescence spectroscopy
AU - Bos, A.
AU - Bos, M.
AU - van der Linden, W.E.
PY - 1993
Y1 - 1993
N2 - The performance of artificial neural networks (ANNs) for modeling the Cr---Ni---Fe system in quantitative x-ray fluorescence spectroscopy was compared with the classical Rasberry-Heinrich model and a previously published method applying the linear learning machine in combination with singular value decomposition. Apart from determining if ANNs were capable of modeling the desired non-linear relationships, also the effects of using non-ideal and noisy data were studied. For this goal, more than a hundred steel samples with large variations in composition were measured at their primary and secondary K¿ and Kß lines. The optimal calibration parameters for the Rasberry-Heinrich model were found from this dataset by use of a genetic algorithm. ANNs were found to be robust and to perform generally better than the other two methods in calibrating over large ranges.
AB - The performance of artificial neural networks (ANNs) for modeling the Cr---Ni---Fe system in quantitative x-ray fluorescence spectroscopy was compared with the classical Rasberry-Heinrich model and a previously published method applying the linear learning machine in combination with singular value decomposition. Apart from determining if ANNs were capable of modeling the desired non-linear relationships, also the effects of using non-ideal and noisy data were studied. For this goal, more than a hundred steel samples with large variations in composition were measured at their primary and secondary K¿ and Kß lines. The optimal calibration parameters for the Rasberry-Heinrich model were found from this dataset by use of a genetic algorithm. ANNs were found to be robust and to perform generally better than the other two methods in calibrating over large ranges.
U2 - 10.1016/0003-2670(93)80441-M
DO - 10.1016/0003-2670(93)80441-M
M3 - Article
SN - 0003-2670
VL - 277
SP - 289
EP - 295
JO - Analytica chimica acta
JF - Analytica chimica acta
IS - 2
ER -