光谱学与光谱分析 |
|
|
|
|
|
The Application of Improved GMDH Network to the Portable X-Ray Fluorescence Analyzer |
LI Fei, GE Liang-quan*, LUO Yao-yao, ZHANG Qing-xian, GU Yi |
Chengdu University of Technology, Chengdu 610059,China |
|
|
Abstract The fundamental parameter method, empirical coefficient method, artificial neural network and some other methods are commonly used to establish the physical model between the count rate and the content of elements in the energy dispersive X-ray fluorescence analysis technique. Besides, through a large number of theoretical and experimental proof, as a new method of dealing with complex nonlinear problems, GMDH (group method of data handing) is better than most of statistical methods of calculation. And is a self-organizing learning in feed forward network, which could auto filter and determine its structure in the training process. Here, we are going to improve GMDH and give a quantitative prediction of the results. And both the reference values and forecast values of relative errors will be less than 5%, which make the method simple, reasonable, and reliable.
|
Received: 2012-10-08
Accepted: 2013-01-29
|
|
Corresponding Authors:
GE Liang-quan
E-mail: glq@cdut.edu.cn
|
|
[1] ZHANG Qiu-ju, ZHU Bang-zhu(张秋菊,朱帮助). J. Zhengzhou Univ.(郑州大学学报),2010,42(1):9. [2] Angeyo K H, Gari S, Mustapha A O, et al. Applied Radiation and Isotopes, 2012, (70): 2596. [3] Li F, Gardner R P. Appl. Radiat. Isotopes, 2012, (70): 1243. [4] Sabriye Seven. Radiation Physics and Chemistry, 2012, (81): 489. [5] JING Ke-qiu, BIAO Deng, QUN Yang, et al. Nuclear Instruments and Methods in Physics Research B, 2011, (269): 2662. [6] WANG Yi,LI Qin,JIANG Xiao-guo(王 毅,李 勤,江孝国). Chinese Physics C(中国物理C),2012,36(9):861. [7] SHI Ji-yong,ZOU Xiao-bo,ZHAO Jie-wen,et al(石吉勇,邹小波,赵杰文,等). J. Infrared Millim. Waves(红外与毫米波学报),2011,30(5):458. [8] CHEN Hua-gen,LI Jia-xiao,WU Jian-sheng,et al(陈华根,李嘉虓,吴健生,等). Chinese Journal of Geophysics(地球物理学报),2011,55(2):663. [9] LI Jian-hui,ZHU Zi-qiang,LIU Shu-cai,et al(李建慧,朱自强,刘树才,等). Oil Geophysical Prospecting(石油地球物理勘探),2011,46(1):138. [10] ZHANG Hu,JIANG Jian-jun,JIANG Xian-yi(张 虎,姜建军,蒋先艺). Oil Geophysical Prospecting(石油地球物理勘探),2011,46(1):12. [11] YI Jun,SHI Wei-ren(易 军,石为人). Acta Electronica Sinica(电子学报),2010,38(6):1239. [12] Aguilera J A,Aragon C,Madurga V,et al. Spectrochimica Acta Part B,2009,64: 993. |
[1] |
ZHEN Huan-yi, MA Rui-jun*, CHEN Yu*, SUN Xiao-peng, MA Chuang-li. Study on Prediction Model of Malathion Pesticide Concentration Absorption Spectra Based on CARS and K-S[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(05): 1601-1606. |
[2] |
YANG Tian-wei1, 2, ZHANG Ji2, 3, LI Jie-qing1, WANG Yuan-zhong2, 3*, LIU Hong-gao1*. Fourier transform infrared (FTIR) spectroscopy; Bolete mushrooms; Cadmium; Content prediction; Discrimination[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(09): 2730-2736. |
[3] |
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(05): 1410-1412. |
[4] |
CHEN Guo-qing, WEI Bai-lin, WANG Jun, WU Ya-min, GAO Shu-mei, KONG Yan, ZHU Tuo* . Quantitative Determination of Melamine by Fluorescence Spectroscopy and Radial Basis Function Neural Networks [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2010, 30(01): 239-242. |
[5] |
YU Xiao-hui1,ZHANG Zhuo-yong1*,MA Qun2,FAN Guo-qiang2. Quantitative Prediction of Active Constituents in Rhubarb by Near Infrared Spectroscopy and Radial Basis Function Neural Networks[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2007, 27(03): 481-485. |
|
|
|
|