Self-adaptive spatial-temporal network based on heterogeneous data for air quality prediction
With the development of society and the rise of people's environmental awareness, air pollution is receiving increased public attention. Accurate air quality prediction can provide useful information for government decision-making and residents' activities. However, accurately predicting f...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2021-07-01
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| Series: | Connection Science |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/09540091.2020.1841095 |