Research on the Application of Improved M-P Neural Network to the Determination of Lead and Zinc Ore Element Contents by Energy Disperse X-Ray Fluorescence Analysis
LI Fei, GE Liang-quan*, ZHANG Qing-xian, GU Yi, WAN Zhi-xiong, LI Wang-yan
Chengdu University of Technology, Chengdu 610059, China
Abstract：Because of different constraints (such as different kinds of measurable elements, characteristic X-ray energy, changes in matrix composition, etc.), usually it’s not easy to get accurate information of elements, resulting in mistakes in later data analysis of energy disperse X-ray fluorescence measurement. The method is based on McCulloch-Pitts neural network (M-P neural network), according to matrix effect, to establish a new neural network model for quantitative forecasting of Zn by taking the data of X-ray fluorescence measurements of Cu, Fe, Pb, etc in lead-zinc mine in western Tianshan as the training sample. The relative error between predicted value and measured value is less than 5%. This method can be more accurate and rapid for X-ray fluorescence; it provides a new approach to correcting information of X-ray fluorescence.
李 飞，葛良全*，张庆贤，谷 懿，万志雄，李王燕 . 改进型M-P神经网络在能量色散X荧光分析测定铅锌矿元素含量的应用研究 [J]. 光谱学与光谱分析, 2012, 32(05): 1410-1412.
LI Fei, GE Liang-quan*, ZHANG Qing-xian, GU Yi, WAN Zhi-xiong, LI Wang-yan . Research on the Application of Improved M-P Neural Network to the Determination of Lead and Zinc Ore Element Contents by Energy Disperse X-Ray Fluorescence Analysis. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32(05): 1410-1412.
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