[1] Deng T, Yu Y. Research on ore identification and separation based on improved PSO-Faster R-CNN algorithm[J]. Mining Research and Development, 41, 178-182(2021).

[2] Yang Y W, Li C, Liu S et al. Classification and identification of brands of iron ores using laser-induced breakdown spectroscopy combined with principal component analysis and artificial neural networks[J]. Analytical Methods, 12, 1316-1323(2020).

[3] Hu Y, Fan Z W, Li C et al. Laser-induced breakdown spectroscopy combined with extreme learning machine mineral identification analysis research[J]. Spectroscopy and Spectral Analysis, 36, 471-472(2016).

[4] Dong P K, Zhao S Y, Zheng K X et al. Rapid identification of ginseng origin by laser induced breakdown spectroscopy combined with neural network and support vector machine algorithm[J]. Acta Physica Sinica, 70, 040201(2021).

[5] Li A Z, Wang X S, Xu X J et al. Fast classification of tobacco based on laser-induced breakdown spectroscopy[J]. Chinese Optics, 12, 1139-1146(2019).

[6] Zhou Z H, Tian X Y, Sun L X et al. Identification of aluminum alloy grades by fiber-laser induced breakdown spectroscopy combined with support vector machine[J]. Laser & Optoelectronics Progress, 55, 063002(2018).

[7] Yang C R. Study of the spectral data processing in laser induced breakdown spectroscopy technology[D], 26-31(2014).

[8] Sheng L W, Zhang T L, Niu G H et al. Classification of iron ores by laser-induced breakdown spectroscopy (LIBS) combined with random forest (RF)[J]. Journal of Analytical Atomic Spectrometry, 30, 453-458(2015).

[9] Képeš E, Vrábel J, Střítežská S et al. Benchmark classification dataset for laser-induced breakdown spectroscopy[J]. Scientific Data, 7, 53(2020).

[10] Kennedy J, Eberhart R. Particle swarm optimization[C], 1942-1948(1995).

[11] García-Gonzalo E, Fernández-Martínez J L. A brief historical review of particle swarm optimization (PSO)[J]. Journal of Bioinformatics and Intelligent Control, 1, 3-16(2012).

[12] Marini F, Walczak B. Particle swarm optimization (PSO). A tutorial[J]. Chemometrics and Intelligent Laboratory Systems, 149, 153-165(2015).

[13] Tang Y Q, Li C H, Song Y F. Network security situation prediction based on improved particle swarm optimization and extreme learning machine[J]. Journal of Computer Applications, 41, 768-773(2021).

[14] Su Y X. Sound event recognition based on adaptive particle swarm optimized matching tracking[J]. Laser & Optoelectronics Progress, 57, 101502(2020).

[15] Shi Y, Eberhart R C. Empirical study of particle swarm optimization[C], 1945-1950(1999).

[16] Yang Y L, Wang P, Ma C H. Quantitative analysis of Mn element in liquid steel by LIBS based on particle swarm optimized support vector machine[J]. Laser & Optoelectronics Progress, 52, 073004(2015).

[17] Subasi A. Classification of EMG signals using PSO optimized SVM for diagnosis of neuromuscular disorders[J]. Computers in Biology and Medicine, 43, 576-586(2013).

[18] Yang Y S, Zhang Y, Yang Y L et al. Qualitative analysis of molten steel based on support vector machine by LIBS[J]. Laser & Optoelectronics Progress, 52, 053001(2015).

[19] Sha W, Li J T, Lu C P. Quantitative analysis of Mn in soil based on laser-induced breakdown spectroscopy optimization[J]. Chinese Journal of Lasers, 47, 0511001(2020).

[20] Liu J X, Du B, Deng Y Q et al. Terahertz-spectral identification of organic compounds based on differential PCA-SVM method[J]. Chinese Journal of Lasers, 46, 0614039(2019).

[21] Wang S T, Wu X, Zhu W H et al. Fluorescence detection of polycyclic aromatic hydrocarbons by parallel factor combined with support vector machine[J]. Acta Optica Sinica, 39, 0530002(2019).