[1] He Feng. Prediction of unburned carbon in flue dust and evaluation of measurement uncertainty[J]. Industrial Control Computer, 33, 21-23(2020).

[2] Cheng Qiming, Hu Xiaoqing, Wang Yingfei, et al. Summary of measurement methods of carbon in fly ash[J]. Journal of Shanghai University of Electric Power, 27, 519-524(2011).

[3] Wang Z, Yuan T B, Hou Z Y, et al. Laser-induced breakdown spectroscopy in China[J]. Frontiers of Physics, 9, 419-438(2014).

[4] Deguchi Y, Noda M, Fukuda Y, et al. Industrial applications of temperature and species concentration monitoring using laser diagnostics[J]. Journal of Bacteriology, 190, 2637-2641(2002).

[5] Noda M. Detection of carbon content in a high-temperature and high-pressure environment using laser-induced breakdown spectroscopy[J]. Spectrochim Acta Part B, 57, 701-709(2002).

[6] Kurihara M, Ikeda K, Izawa Y, et al. Optimal boiler control through real-time monitoring of unburned carbon in fly ash by laser-induced breakdown spectroscopy[J]. Applied Optics, 42, 6159-6165(2003).

[7] Blevins L G, Shaddix C R, Sickafoose S M, et al. Laser-induced breakdown spectroscopy at high temperatures in industrial boilers and furnaces[J]. Applied Optics, 42, 6107-6118(2003).

[8] Li Yufang, Zhang Lei, Gong Yao, et al. Development of a laser on-line cement raw material analysis equipment[J]. Spectroscopy and Spectral Analysis, 36, 1494-1499(2016).

[9] Zhang Xinhua, She Mingjun, Zhang Yanshu, et al. The progress and potential of the application of laser technology in mud logging[J]. Petroleum Drilling Techniques, 46, 111-117(2018).

[10] Body D, Chadwick B L. Optimization of the spectral data processing in a LIBS simultaneous elemental analysis system[J]. Spectrochimica Acta Part B Atomic Spectroscopy, 56, 725-736(2001).

[11] Body D, Chadwick B L. Simultaneous elemental analysis system using laser induced breakdown spectroscopy[J]. Review of Scientific Instruments, 72, 1625-1629(2001).

[12] Chadwick B L, Body D. Development and commercial evaluation of laser-induced breakdown spectroscopy chemical analysis technology in the coal power generation industry[J]. Applied Spectroscopy, 56, 70-74(2002).

[13] Dong M R, Lu J D, Yao S C, et al. Application of LIBS for direct determination of volatile matter content in coal[J]. Journal of Analytical Atomic Spectrometry, 26, 2183-2188(2011).

[14] Dong Meirong, Wei Liping, Lu Jidong, et al. Quantitative analysis of LIBS coal heat value based on K-CV parameter optimization support vector machine[J]. Spectroscopy and Spectral Analysis, 39, 2202-2209(2019).

[15] Dong M R, Wei L P, Lu J D, et al. A comparative model combining carbon atomic and molecular emissions based on partial least squares and support vector regression correction for carbon analysis in coal using LIBS[J]. Journal of Analytical Atomic Spectrometry, 34, 480-488(2019).

[16] Wang Z, Feng J, Li L Z, et al. A multivariate model based on dominant factor for laser-induced breakdown spectroscopy measurements[J]. Journal of Analytical Atomic Spectrometry, 26, 2289-2299(2011).

[17] Yan C, Qi J, Ma J, et al. Determination of carbon and sulfur content in coal by laser induced breakdown spectroscopy combined with kernel-based extreme learning machine[J]. Chemometrics and Intelligent Laboratory Systems, 167, 226-231(2017).

[18] Wang Z Z, Liu R W, Deguchi Y, et al. Detection improvement of unburned carbon content in fly ash flow using LIBS with a two-stage cyclone measurement system[J]. Energy & Fuels, 33, 7805-7812(2019).

[19] Yao S C, Xu J L, Zhao J B, et al. Characterization of fly ash laser-induced plasma for improving the on-line measurement of unburned carbon in gas–solid flow[J]. Energy & Fuels, 31, 4681-4686(2017).

[20] Yao S C, Lu J D, Zheng J P, et al. Analyzing unburned carbon in fly ash using laser-induced breakdown spectroscopy with multivariate calibration method[J]. Journal of Analytical Atomic Spectrometry, 27, 473-478(2012).

[21] Yao Shunchun, Lu Jidong, Pan Shenghua, et al. Coal suitability of the measurement of unburned carbon by laser-induced breakdown spectroscopy[J]. Proceedings of The Chinese Society for Electrical Engineering, 29, 80-83(2009).

[22] Yao Shunchun, Lu Jidong, Dong Meirong, et al. Simultaneous measurements of coal ash compositionby laser-induced breakdown spectroscopy in different optical collection[J]. Proceedings of The Chinese Society for Electrical Engineering, 33, 54-60(2013).

[23] Hu Ruomu, Wang Zhenzhen, Liu Renwei, et al. Quantitative analysis of unburned carbon in fly ash by laser-induced breakdown spectroscopy[J]. Acta Photonica Sinica, 47, 39-46(2018).

[24] Shen Yueliang, Yao Shunchun, Pan Gang, et al. Influence of binder on laser-induced breakdown spectroscopy measurement of unburned carbon in fly ash[J]. Chinese Journal of Lasers, 41, 242-246(2014).

[25] Zhang Lei, Ma Weiguang, Dong Lei, et al. Development of an apparatus for on-line analysis of unburned carbon in fly ash using laser-induced breakdown spectroscopy (LIBS)[J]. Appl Spectrosc, 65, 790-796(2011).

[26] Liu Renwei, Deguchi Y, Nan Weigang, et al. Unburned carbon measurement in fly ash using laser-induced breakdown spectroscopy with short nanosecond pulse width laser[J]. Advanced Powder Technology, 30, 1210-1218(2019).

[27] Huang J, Dong M, Lu S, et al. Estimation of the mechanical properties of steel via LIBS combined with canonical correlation analysis (CCA) and support vector regression (SVR)[J]. Journal of Analytical Atomic Spectrometry, 33, 720-729(2018).

[28] Lu S, Shen S, Huang J, et al. Feature selection of laser-induced breakdown spectroscopy data for steel aging estimation[J]. Spectrochimica Acta Part B Atomic Spectroscopy, 150, 49-58(2018).

[29] Wang Huiwen, Meng Jie. Predictive modeling on multivariate linear regression[J]. Journal of Beijing University of Aeronautics and Astronautics, 33, 500-504(2007).

[30] [30] Wang Huiwen. Partial LeastSquares RegressionMethod Applications[M]. Beijing: National Defense Industry Press, 1999: 150197. (in Chinese)

[31] Huang Guangbin, Wang Dianhui, Lan Yuan. Extreme learning machines: A survey[J]. International Journal of Machine Learning and Cybernetics, 2, 107-122(2011).

[32] Li X H, Yang S B, Fan R W, et al. Discrimination of soft tissues using laser-induced breakdown spectroscopy in combination with k nearest neighbors (kNN) and support vector machine (SVM) classifiers[J]. Optics & Laser Technology, 102, 233-239(2018).

[33] Yu L, Liu H. Efficient feature selection via analysis of relevance and redundancy[J]. Journal of Machine Learning Research, 5, 1205-1224(2004).

[34] Guyon I, Elisseeff A. An introduction to variable and feature selection[J]. Journal of Machine Learning Research, 3, 1157-1182(2003).

[35] Dingari N C, Barman I, Myakalwar A K, et al. Incorporation of support vector machines in the LIBS toolbox for sensitive and robust classification amidst unexpected sample and system variability[J]. Analytical Chemistry, 84, 2686-2694(2012).

[36] Song L J, Huang W K, Han X, et al. Real-time composition monitoring using support vector regression of laser-induced plasma for laser additive manufacturing[J]. IEEE Transactions on Industrial Electronics, 64, 633-642(2016).