Application of RBF Network for Correction of Nonlinear Matrix Effects in Geological Samples

详细信息   

• 责任者：Yan Yusheng (College of Information Engineering ; Chengdu University of Technology ; Chengdu 610059 ; China) ; Yang Xuemei
• 刊名：Computing Techniques for Geophysical and Geochemical Exploration
• 出版年：2008
• 卷期：30(2)
• 关键词：X射线荧光 ; X—ray fluorescence ; 神经网络系统 ; neural network systems
• 页码：p.169-172
• 图表：3 illus., 2 tables, 10 refs.
• 分类号：0900
• issnNo：ISSN1001-1749
• isbnNo：CN51-1242/P

摘要

The orthogonal least-squares algorithm of the RBF network is applied to dynamic correction of the nonlinear matrix effect in the geological samples of Panzhihua. First the EDXRF instrument is used to measure the samples, and then the fluorescence counting of samples is normalized. The two cascaded framework of auto classify model and dynamic correction the nonlinear matrix effect model is designed, and then the self- organizing network is adopted to classify and the RBF network is used to forecast the content of Ti in the unknown sample. The results show that the error of forecast content of Ti comprising to the chemistry analysis is lower of 0.5%, which suggests that the RBF network can effectively correct the nonlinear matric effect to the geological samples, and can achieve the request of the mine production.