Automatic variable selection method and a comparison for quantitative analysis in laser-induced breakdown spectroscopy

作者：Duan, Fajie; Fu, Xiao^*; Jiang, Jiajia; Huang, Tingting; Ma, Ling; Zhang, Cong

来源：Spectrochimica Acta Part B: Atomic Spectroscopy , 2018, 143: 12-17.

DOI：10.1016/j.sab.2018.02.010

• LIBS
• Quantitative analysis
• Variable selection
• Genetic algorithm
• Successive projections algorithm

In this work, an automatic variable selection method for quantitative analysis of soil samples using laser-induced breakdown spectroscopy (LIBS) is proposed, which is based on full spectrum correction (FSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS). The method features automatic selection without artificial processes. To illustrate the feasibility and effectiveness of the method, a comparison with genetic algorithm (GA) and successive projections algorithm (SPA) for different elements (copper, barium and chromium) detection in soil was implemented. The experimental results showed that all the three methods could accomplish variable selection effectively, among which FSC-mIPW-PLS required significantly shorter computation time (12s approximately for 40,000 initial variables) than the others. Moreover, improved quantification models were got with variable selection approaches. The root mean square errors of prediction (RMSEP) of models utilizing the new method were 27.47 (copper), 37.15 (barium) and 39.

• 出版日期2018-5
• 单位天津大学; 清华大学