• Spectroscopy and Spectral Analysis
  • Vol. 32, Issue 5, 1410 (2012)
LI Fei*, GE Liang-quan, ZHANG Qing-xian, GU Yi, WAN Zhi-xiong, and LI Wang-yan
Author Affiliations
  • [in Chinese]
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    DOI: 10.3964/j.issn.1000-0593(2012)05-1410-03 Cite this Article
    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[J]. Spectroscopy and Spectral Analysis, 2012, 32(5): 1410 Copy Citation Text show less

    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.
    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[J]. Spectroscopy and Spectral Analysis, 2012, 32(5): 1410
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