A balanced social LSTM for PM2.5 concentration prediction based on local spatiotemporal correlation

被引：0
|
作者：
Shi, Lukui [1 ,2 ]
Zhang, Huizhen [1 ,2 ]
Xu, Xia [3 ]
Han, Ming [4 ]
Zuo, Peiliang [5 ]
机构：
[1] School of Artificial Intelligence, Hebei University of Technology, Tianjin,300401, China
[2] Hebei Province Key Laboratory of Big Data Calculation, Tianjin,300401, China
[3] College of Computer Science, Nankai University, Tianjin,300071, China
[4] School of Computer Science and Engineering, Shijiazhuang University, Shijiazhuang,050035, China
[5] Department of Electronic and Communication Engineering, Beijing Institute of Electronic Science and Technology, Beijing,100070, China
来源：
Chemosphere | 2022年 / 291卷
基金：
中国国家自然科学基金;
关键词：
'current - Concentration prediction - Hot topics - Mean squared error - PM 2.5 - PM2.5 concentration prediction - Pollution prevention - Prediction-based - Spatial interaction - Spatiotemporal correlation;
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摘要：
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