Jing Liang

A novel hybrid feature selection strategy in quantitative analysis of laser-induced breakdown spectroscopy

Chunhua Yan, Jing Liang, Mingjing Zhao et al. · Analytica Chimica Acta · 2019 · 83 citations

Engineering, Optical Diagnostics, Spectroscopy +5

Determination of coal properties using laser-induced breakdown spectroscopy combined with kernel extreme learning machine and variable selection

Chunhua Yan, Juan Qi, Jing Liang et al. · Journal of Analytical Atomic Spectrometry · 2018 · 43 citations

Clean Coal Technology, Engineering, Machine Learning +9

Data fusion of laser induced breakdown spectroscopy (LIBS) and infrared spectroscopy (IR) coupled with random forest (RF) for the classification and discrimination of compound salvia miltiorrhiza

Jing Liang, Maogang Li, Yao Du et al. · Chemometrics and Intelligent Laboratory Systems · 2020 · 41 citations

Engineering, Optical Diagnostics, Spectroscopy +10

Rapid discrimination of Salvia miltiorrhiza according to their geographical regions by laser induced breakdown spectroscopy (LIBS) and particle swarm optimization-kernel extreme learning machine (PSO-KELM)

Jing Liang, Chunhua Yan, Ying Zhang et al. · Chemometrics and Intelligent Laboratory Systems · 2020 · 35 citations

Botany, Plant Pathology, Salvia Miltiorrhiza +2

Quantitative analysis of coal quality by mutual information-particle swarm optimization (MI-PSO) hybrid variable selection method coupled with spectral fusion strategy of laser-induced breakdown spectroscopy (LIBS) and fourier transform infrared spectroscopy (FTIR)

Jing Liang, Hongsheng Tang, Tianlong Zhang et al. · Spectrochimica Acta Part B Atomic Spectroscopy · 2021 · 34 citations

Clean Coal Technology, Engineering, Quantitative Analysis +3