Spatiotemporal Deep Learning Model for Citywide Air Pollution Interpolation and Prediction

Air pollution prediction for the whole city is a challenging problem. The reason is, there are many spatiotemporal factors affecting air pollution throughout the city. Collecting as many of them could help us to forecast air pollution better. In this research, we present many spatiotemporal datasets...

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Veröffentlicht in:	International Conference on Big Data and Smart Computing S. 55 - 62
Hauptverfasser:	Le, Van-Duc, Bui, Tien-Cuong, Cha, Sang-Kyun
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.02.2020
Schlagworte:	Air pollution Atmospheric modeling citywide deep learning Interpolation prediction Predictive models spatiotemporal Spatiotemporal phenomena Tensile stress Urban areas
ISSN:	2375-9356
Online-Zugang:	Volltext
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