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| Action | Date | Notes | Link |
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| article pdf uploaded. | 22 November 2025 10:21 CET | Version of Record | https://www.mdpi.com/2073-4433/16/12/1317/pdf |
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| Action | Date | Notes | Link |
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| article pdf uploaded. | 22 November 2025 10:21 CET | Version of Record | https://www.mdpi.com/2073-4433/16/12/1317/pdf |
Tang, Y.; Deng, J.; Cui, X.; Liu, Z.; Yang, L.; Zhang, S.; Liang, Y. High-Resolution Spatial Prediction of Daily Average PM2.5 Concentrations in Jiangxi Province via a Hybrid Model Integrating Random Forest and XGBoost. Atmosphere 2025, 16, 1317. https://doi.org/10.3390/atmos16121317
Tang Y, Deng J, Cui X, Liu Z, Yang L, Zhang S, Liang Y. High-Resolution Spatial Prediction of Daily Average PM2.5 Concentrations in Jiangxi Province via a Hybrid Model Integrating Random Forest and XGBoost. Atmosphere. 2025; 16(12):1317. https://doi.org/10.3390/atmos16121317
Chicago/Turabian StyleTang, Yuming, Jing Deng, Xinyi Cui, Zuhan Liu, Liu Yang, Shaoquan Zhang, and Yeheng Liang. 2025. "High-Resolution Spatial Prediction of Daily Average PM2.5 Concentrations in Jiangxi Province via a Hybrid Model Integrating Random Forest and XGBoost" Atmosphere 16, no. 12: 1317. https://doi.org/10.3390/atmos16121317
APA StyleTang, Y., Deng, J., Cui, X., Liu, Z., Yang, L., Zhang, S., & Liang, Y. (2025). High-Resolution Spatial Prediction of Daily Average PM2.5 Concentrations in Jiangxi Province via a Hybrid Model Integrating Random Forest and XGBoost. Atmosphere, 16(12), 1317. https://doi.org/10.3390/atmos16121317