The extreme gradient boosting (XGBoost) ensemble learning algorithm excels in solving complex nonlinear relational problems. In order to accurately predict the surface subsidence caused by mining, this work introduces the genetic algorithm (GA) and XGBoost integrated algorithm model for mining subsidence prediction and uses the Python language to develop the GA-XGBoost combined model. The hyperparameter vector of XGBoost is optimized by a genetic algorithm to improve the prediction accuracy and reliability of the XGBoost model. Using some domestic mining subsidence data sets to conduct a model prediction evaluation, the results show that the R2 (coefficient of determination) of the prediction results of the GA-XGBoost model is 0.941, the RMSE (root mean square error) is 0.369, and the MAE (mean absolute error) is 0.308. Then, compared with classic ensemble learning models such as XGBoost, random deep forest, and gradient boost, the GA-XGBoost model has higher prediction accuracy and performance than a single machine learning model.

Changbai jade is a type of jade ore with good economic value that is found in the tuff of the Upper Triassic Changbai Formation of the Mesozoic period in Jilin Province, China. However, the mineral composition of the kaolinite group in Changbai Jade has not been definitively identified, and there has been a lack of systematic mineralogical and spectral analysis. To analyze the mineralogical and spectroscopic characteristics of Changbai jade, this study utilized several modern testing methods, including X-ray fluorescence spectrometry (XRF), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectrometry (EDS), Fourier transform infrared absorption spectroscopy (FTIR), Raman spectrum test (Raman), and Ultraviolet visible (UV-vis). Mineralogical and spectroscopic analyses were conducted on Changbai jade ore samples CB21 and CB22. The results indicated that the main metamorphic minerals of the two samples are dickite and the color-causing factor of the yellow part is pyrite. This research provides basic theoretical research data for jade processing technology and the geological origin of Changbai jade.