Spectroscopy and Spectral Analysis, Volume. 40, Issue 12, 3812(2020)

Quantitative Analysis of Cu and Ni in Oil-Contaminated Soil by LIBS Combined With Variable Selection Method and PLS

Shao-nong ZHU1,1、*, Yu DING1,1, Yu-juan CHEN1,1, Fan DENG1,1, Fei-fan CHEN1,1, and Fei YAN1,1
Author Affiliations
  • 1[in Chinese]
  • 11. Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science & Technology, Nanjing 210044, China
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    Figures & Tables(14)
    Experimental setup
    Typical spectra of soil samples
    RMSECVs for PLS models with different potential variables of Cu and Ni
    Prediction results of PLS for calibration set
    Prediction results of PLS for test set
    Prediction results of iPLS for calibration set
    Prediction results of iPLS for test set
    Prediction results of BiPLS for calibration set
    Prediction results of BiPLS for test set
    • Table 1. The Contents list of Cu and Ni (%)

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      Table 1. The Contents list of Cu and Ni (%)

      编号CuNi编号CuNi
      10.450.6590.570.77
      20.510.71100.780.98
      30.480.68110.811.01
      40.540.74120.750.95
      50.520.72130.931.13
      60.600.80141.051.25
      70.660.86151.221.42
      80.720.92160.821.02
    • Table 2. RMSECVs for iPLS models with different interval numbers of Cu

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      Table 2. RMSECVs for iPLS models with different interval numbers of Cu

      区间个数区间序号RMSECV变量个数
      1070.023 3582
      1160.033 5529
      1250.026 0485
      1350.026 9448
      14110.036 5415
      15100.023 3388
      1660.034 8364
      1760.026 2343
      1890.019 7324
      1990.018 6306
      20100.020 3291
      21100.019 0277
      22110.020 1265
      23150.019 7253
      24120.020 4242
      25250.031 8232
    • Table 3. RMSECVs for BiPLS with different interval numbers of Cu

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      Table 3. RMSECVs for BiPLS with different interval numbers of Cu

      区间个数最小RMSECV区间个数变量数
      100.023 31582
      110.020 852 645
      120.022 141 940
      130.022 452 238
      140.018 462 494
      150.025 462 327
      160.019 8103 639
      170.019 082 739
      180.020 692 910
      190.018 992 756
      200.022 172 037
      210.014 371 940
      220.015 441 059
      230.015 1102 530
      240.015 8102 424
      250.016 192 094
    • Table 4. Comparison of PLS, iPLS and BiPLS models for Cu element

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      Table 4. Comparison of PLS, iPLS and BiPLS models for Cu element

      算法类别变量数量校正集测试集
      RC2RMSECRP2RMSEPRPD
      PLS5 8190.978 40.034 20.930 00.041 82.5
      iPLS2530.998 10.010 30.865 70.053 82.8
      BiPLS1 9400.996 30.014 10.944 90.036 33.0
    • Table 5. Comparison of PLS, iPLS and BiPLS models for Ni element

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      Table 5. Comparison of PLS, iPLS and BiPLS models for Ni element

      算法类别变量数量校正集测试集
      RC2RMSECRP2RMSEPRPD
      PLS5 8190.685 50.148 80.797 30.181 50.3
      iPLS2530.997 90.010 60.830 40.060 72.5
      BiPLS1 9400.994 40.017 50.933 70.041 42.6
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    Shao-nong ZHU, Yu DING, Yu-juan CHEN, Fan DENG, Fei-fan CHEN, Fei YAN. Quantitative Analysis of Cu and Ni in Oil-Contaminated Soil by LIBS Combined With Variable Selection Method and PLS[J]. Spectroscopy and Spectral Analysis, 2020, 40(12): 3812

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    Paper Information

    Category: Research Articles

    Received: Dec. 18, 2019

    Accepted: --

    Published Online: Jun. 18, 2021

    The Author Email: Shao-nong ZHU (shaonong_zhu@nuist.edu.cn)

    DOI:10.3964/j.issn.1000-0593(2020)12-3812-06

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