Extraction of multi-scale features enhances the deep learning-based daily PM2.5 forecasting in cities

被引：0
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作者：
Dong, Liang [1 ]
Hua, Pei [2 ,3 ]
Gui, Dongwei [5 ]
Zhang, Jin [4 ,5 ]
机构：
[1] South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou,510535, China
[2] SCNU Environmental Research Institute, Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety & MOE Key Laboratory of Theoretical Chemistry of Environment, South China Normal University, Guangzhou,510006, China
[3] School of Environment, South China Normal University, University Town, Guangzhou,510006, China
[4] State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Yangtze Institute for Conservation and Development, Hohai University, Nanjing,210098, China
[5] State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi,830011, China
来源：
Chemosphere | 2022年 / 308卷
基金：
中国国家自然科学基金;
关键词：
46;
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