• Spectroscopy and Spectral Analysis
  • Vol. 42, Issue 9, 2947 (2022)
Rui LI1,1;, Bo LI1,1; *;, Xue-wen WANG1,1;, Tao LIU1,1;..., Lian-jie LI1,1; 2; and Shu-xiang FAN2,2;|Show fewer author(s)
Author Affiliations
  • 11. College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan 030024, China
  • 22. Beijing Research Center of Intelligent Equipment for Agriculture, Beijing 100097, China
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    DOI: 10.3964/j.issn.1000-0593(2022)09-2947-09 Cite this Article
    Rui LI, Bo LI, Xue-wen WANG, Tao LIU, Lian-jie LI, Shu-xiang FAN. A Classification Method of Coal and Gangue Based on XGBoost and Visible-Near Infrared Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2022, 42(9): 2947 Copy Citation Text show less
    References

    [2] C Liu, N Zhang. Scientific Reports, 8, 190(2018).

    [4] R Hu, H Wang S, Y Zhao et al. Chinese Journal of Analytical Chemistry, 47, E19034(2019).

    [7] S Ge, S Wang, E Yang et al. Journal of Spectroscopy, 2018, 2754908(2018).

    [8] T Le B, Y Mao, D Xiao et al. Optics and Laser Technology, 114, 10(2019).

    [9] H Li, X Sun, D Xiao. ACS Omega, 5, 25772(2020).

    [10] F Hu, P Yan, M Zhou et al. IEEE Access, 7, 169697(2019).

    [11] T Chen, C Guestrin. XGBoost: A Scalable Tree Boosting System. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 785(2016).

    Rui LI, Bo LI, Xue-wen WANG, Tao LIU, Lian-jie LI, Shu-xiang FAN. A Classification Method of Coal and Gangue Based on XGBoost and Visible-Near Infrared Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2022, 42(9): 2947
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