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Focusing on one component each time—comparison of single and multiple component prediction algorithms in artificial neural networks for x-ray fluorescence analysis

✍ Scribed by Liqiang Luo; Ang Ji; Guangzu Ma; Changlin Guo


Publisher
John Wiley and Sons
Year
1998
Tongue
English
Weight
438 KB
Volume
27
Category
Article
ISSN
0049-8246

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✦ Synopsis


An algorithm of single component prediction based on backward error propagation 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 predictive accuracy of the single component prediction algorithm was superior to that of the multiple component prediction model. The e †ects of overÐtting, standard samples and model parameters on the predictive accuracy were also examined.