FOCUSING ON ONE-COMPONENT EACH TIME - COMPARISON OF SINGLE AND MULTIPLE COMPONENT PREDICTION ALGORITHMS IN ARTIFICIAL NEURAL NETWORKS FOR X-RAY-FLUORESCENCE ANALYSIS

An algorithm of single component prediction based on backward error pr opagation is proposed, in,which only one component concentration in a multivariate system is predicted each time. The algorithm was compared with a multiple component prediction model. In general, the predictiv e accuracy of the single component prediction algorithm was superior t o that of the multiple component prediction model. The effects of over fitting, standard samples and model parameters on the predictive accur acy were also examined. (C) 1998 John Wiley & Sons, Ltd.