• Chinese Optics Letters
  • Vol. 12, Issue s2, S23001 (2014)
Wei Zhang1, Lianfei Duan1, Luozheng Zhang1, Yujun Zhang2, Liuyi Ling2, and Yunjun Yang1
Author Affiliations
  • 1New Star Research Institute of Applied Technology, Hefei 230031, China
  • 2Key Laboratory of Environment Optics and Technology, Anhui Institute of Optics and Fine Mechanics, the Chinese Academy of Sciences, Hefei 230031, China
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    DOI: 10.3788/col201412.s23001 Cite this Article Set citation alerts
    Wei Zhang, Lianfei Duan, Luozheng Zhang, Yujun Zhang, Liuyi Ling, Yunjun Yang. X-ray fluorescence spectra quantitative analysis based on characteristic spectra optimization of partial least-squares method[J]. Chinese Optics Letters, 2014, 12(s2): S23001 Copy Citation Text show less
    References

    [1] A. Ji, G. Y. Tao, S. J. Zhuo, and L. Q. Luo, X-ray Fluorescence Spectra Analysis (Science Press, 2003).

    [2] R. Jenkins, X-Ray Fluorescence Spectrometry (Wiley, 1999).

    [3] N. Tsoulfanidis, Measurement and Detection of Radiation (Taylor & Francis, 1995).

    [4] Y. Liang, Spectral Analysis Foundation of XRF (Science Press, 2007).

    [5] H. Wold, Path Models with Latent Variables: The NIPALS Approach, Quantitative Sociology: International Perspectives on Mathematical and Statistical Model Building (Academic Press, 1975).

    [6] S. Wold, A. Ruhe, H. Wold, and W. J. Dunn, SIAM J. Sci. Stat. Comput. 5, 735 (1984).

    [7] D. M. Haaland and E. V. Thomas, Am. Chem. Soc. 60, 1192 (1988).

    [8] D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning (Addison-Wesley, 1989).

    [9] A. Popov, Genetic Algorithms for Optimization, User Manual (Hamburg, 2005).

    [10] K. Hasegawa, Y. Miyashita, and K. Funatsu, J. Chem. Inf. Comput. Sci. 37, 306 (1997).

    [11] V. E. Vinzi, W. W. Chin, J. Henseler, and H. Wang, Handbook of Partial Least Squares (Springer-Verlag, 2010).

    Wei Zhang, Lianfei Duan, Luozheng Zhang, Yujun Zhang, Liuyi Ling, Yunjun Yang. X-ray fluorescence spectra quantitative analysis based on characteristic spectra optimization of partial least-squares method[J]. Chinese Optics Letters, 2014, 12(s2): S23001
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