[1] Zhong Y T, Liu X C, Fan Z A et al. Spatiotemporal distribution and inorganic ion concentration of total suspended particles in Tarim Basin in 2009[J]. Journal of Desert Research, 32, 1053-1061(2012).

[2] Feng X J, Geng H, Peng Y et al. Morphology and chemical composition characterization of atmospheric black carbon aerosols during haze events in urban Taiyuan, China[J]. Geochimica, 50, 75-87(2021).

[3] Fougnie B, Chimot J, Vázquez-Navarro M et al. Aerosol retrieval from space–how does geometry of acquisition impact our ability to characterize aerosol properties[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 256, 107304(2020).

[4] Sun C W, Bu Y, Wang Y H et al. Spatial characteristics of spectral intensity of laser induced plasma[J]. Acta Optica Sinica, 41, 2130001(2021).

[5] Tan D Z, Wang Z, Xu B B et al. Photonic circuits written by femtosecond laser in glass: improved fabrication and recent progress in photonic devices[J]. Advanced Photonics, 3, 024002(2021).

[6] Zeng Q W, Liu L, Hu S et al. Nonlinear propagation of intense femtosecond laser pulses in a foggy and cloudy environment[J]. Acta Optica Sinica, 40, 1519001(2020).

[7] Guo W L, Qiu R, Wang C F et al. Detection of chromium in atmospheric aerosol by laser induced breakdown spectroscopy[J]. Chinese Journal of Quantum Electronics, 37, 745-751(2020).

[8] Yan F, Zhu Q B, Huang M et al. Quantitative analysis method for mixture with known components based on Raman spectroscopy[J]. Spectroscopy and Spectral Analysis, 40, 3599-3605(2020).

[9] Chen Y J, Ding Y, Zhu S N et al. Study on quantitative analysis method of silicon in sinter based on neural network and laser-induced breakdown spectroscopy[J]. Metallurgical Analysis, 41, 24-29(2021).

[10] Li Z Y, Zhang H, Nguyen B T T et al. Smart ring resonator-based sensor for multicomponent chemical analysis via machine learning[J]. Photonics Research, 9, B38-B44(2021).

[11] Zhang L. Determination of water pollutant content by near infrared spectroscopy based on convolution neural network[J]. Chemical Analysis and Meterage, 30, 24-27(2021).

[12] Cheng Z, Zhao N J, Yin G F et al. Identification method of planktonic algae community based on multi-task convolutional neural network[J]. Acta Optica Sinica, 42, 0530002(2022).

[13] Li Z W, Cao H, Yang F et al. Research progress of brain tumor segmentation based on convolutional neural network[J]. Laser & Optoelectronics Progress, 58, 2400003(2021).

[14] Yang H Y, Wan Y, Wang Y L et al. Identification of rice diseases based on batch normalization and AlexNet network[J]. Laser & Optoelectronics Progress, 58, 0610007(2021).

[15] Zhang Q, Wei R Y, Yan Q Q et al. Application of deep neural network in quantitative analysis of VOCs by infrared spectroscopy[J]. Spectroscopy and Spectral Analysis, 40, 1099-1106(2020).

[16] Zhang K H, Wang W D, Lv Z Q et al. A CNN-based regression framework for estimating coal ash content on microscopic images[J]. Measurement, 189, 110589(2022).

[17] Du Z H, Meng F L, Li J Y et al. Research on the analytical line auto-selection for quantitative analysis of materials with laser-induced breakdown spectroscopy[J]. Spectroscopy and Spectral Analysis, 32, 876-880(2012).

[18] Zhang X L, Lin T, Xu J F et al. DeepSpectra: an end-to-end deep learning approach for quantitative spectral analysis[J]. Analytica Chimica Acta, 1058, 48-57(2019).

[19] Kingma D P, Ba J. Adam: a method for stochastic optimization[EB/OL]. https://arxiv.org/abs/1412.6980

[20] Liu Y D, Lin X D, Gao H G et al. Quantitative analysis of chlorophyll content in tea leaves by fluorescence spectroscopy[J]. Laser & Optoelectronics Progress, 58, 0830001(2021).