| Citation: | Gong Cheng, Hongrui Zhang, Huan Li, Xiaoqing Deng, Safiyanu Muhammad Elatikpo, Jiaxuan Li, Zhenguang Hu, Guangqiang Li. Quantitative Inversion of REEs in Ion-Adsorbed Rare Earth Ores from the Liutang Area (South China), Based on Measured Hyperspectral Data. Journal of Earth Science, 2023, 34(4): 1068-1082. doi: 10.1007/s12583-021-1504-1
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Rare earth minerals are important strategic resources to economic development all over the world. In this study, multiple linear regression and back propagation (BP) neural network methods are used to invert the contents of ion adsorbed rare earth elements (REEs) and exploring the feasibility of quantitative inversion of REEs through measured hyperspectral data in Liutang rare earth mines, South China. The result shows that the spectral curve of the rare earth ore samples has obvious absorption characteristics around 390, 930, 1 400, 1 900 and 2 200 nm, and continuum removal and the 1st derivative treatment can highlight the absorption characteristics. The modeling accuracies of BP neural network are higher than that of multiple linear regression model. The BP neural network model of the 1st derivative data in 400–1 000 nm bands has the best inversion result of the total content of REEs,
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