• Laser & Optoelectronics Progress
  • Vol. 52, Issue 7, 73004 (2015)
Yang Youliang*, Wang Peng, and Ma Cuihong
Author Affiliations
  • [in Chinese]
  • show less
    DOI: 10.3788/lop52.073004 Cite this Article Set citation alerts
    Yang Youliang, Wang Peng, Ma Cuihong. Quantitative Analysis of Mn Element in Liquid Steel by LIBS Based on Particle Swarm Optimized Support Vector Machine[J]. Laser & Optoelectronics Progress, 2015, 52(7): 73004 Copy Citation Text show less
    References

    [1] Li Junxiang, Yang Youliang, Meng Fanwei, et al.. Matrix correction method used for liquid steel online quantitative analysis by LIBS[J]. Laser & Optoelectronics Progress, 2013, 50(3): 031406.

    [2] Sun Lanxiang, Yu Haibin, Xin Yong, et al.. Quantitative analysis of Mn and Si of alloy steels by laser-induced breakdown spectroscopy[J]. Spectroscopy and Spectral Analysis, 2010, 30(12): 3186-3190.

    [3] Li Min, Zhu Xinyong, Xu Yuan, et al.. Quantitative determination of Cu in lake water by laser induced breakdown spectroscopy[J]. Laser & Optoelectronics Progress, 2013, 50(1): 013001.

    [4] Lin Yongzeng, Yao Mingyin, Chen Tianbing, et al.. Laser induced breakdown spectroscopy of Cu and Cr detection of Gannan navel orange planting soil[J]. Laser & Optoelectronics Progress, 2013, 50(5): 053002.

    [5] Feng Weilei, Wang Fujuan, Zeng Wanqi, et al.. CCD spectrum measurement system for laser induced breakdown spectroscopy[J]. Laser & Optoelectronics Progress, 2013, 50(1): 013002.

    [6] L St-Onge, E Kwong, M Sabsabi, et al.. Quantitative analysis of pharmaceutical products by laser-induced breakdown spectroscopy[J]. Spectrochimica Acta Part B: Atomic Spectroscopy, 2002, 57(7): 1131-1140.

    [7] Li Yujun, Tang Xiaojun, Liu Junhua. Application of least square support vector machine based on particle swarm optimization in quantitative analysis of gas mixture[J]. Spectroscopy and Spectral Analysis, 2010, 30(3): 774-778.

    [8] Ye Meiying, Wang Xiaodong. The support vector machine method of chaotic optical system identification[J]. Acta Optica Sinica, 2004, 24(7): 953-956.

    [9] Wang Chunlong, Liu Jianguo, Zhao Nanjing, et al.. Quantitative analysis of laser-induced breakdown spectroscopy of heavy metals in water based on support-vector-machine regression[J]. Acta Optica Sinica, 2013, 33(3): 0330002.

    [10] Wang Rui. Method analye about support vector machine′s parameter[J]. Journal of Chongqing Normal University (Natural Science Edition), 2007, 24(2): 36-38.

    [11] Gong Yonggang, Tang Shiping. A novel parameters optimization of SVM for large data sets[J]. Computer Simulation, 2010, 27(9): 204-207.

    [12] Yu Shixing. Support Vector Machine (SVM) Based on Intelligent Algorithm Combined With Wood NIR Application Research[D]. Beijing: Beijing Forestry University, 2014.

    [13] Wang Qianqian, Huang Zhiwen, Liu Kai, et al.. Classification of plastics with laser- induced breakdown spectroscopy based on principal component analysis and artificial neural network model[J]. Spectroscopy and Spectral Analysis, 2012, 32(12): 3179-3182.

    CLP Journals

    [1] Wu Yiqing, Sun Tong, Liu Xiuhong, Mo Xinxin, Liu Muhua. Detection of Chromium Content in Soybean Oil by Laser-Induced Breakdown Spectroscopy[J]. Laser & Optoelectronics Progress, 2016, 53(4): 43001

    [2] Yang Youliang, Wang Peng, Ma Cuihong. Quantitative Analysis of Liquid Steel Component by LIBS Based on Improved Multivariate Nonlinear Model[J]. Laser & Optoelectronics Progress, 2016, 53(5): 53002

    [3] Yang Hui, Huang Lin, Liu Muhua, Chen Tianbing, Wang Caihong, Hu Huiqin, Yao Mingyin. Improvement of Analytical Sensitivity on Detecting Cd Residue in Rice by Dual Pulse Laser Induced Breakdown Spectroscopy[J]. Laser & Optoelectronics Progress, 2016, 53(5): 53005

    Yang Youliang, Wang Peng, Ma Cuihong. Quantitative Analysis of Mn Element in Liquid Steel by LIBS Based on Particle Swarm Optimized Support Vector Machine[J]. Laser & Optoelectronics Progress, 2015, 52(7): 73004
    Download Citation