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About Adaptive Deep Learning-Based Air Quality Prediction Model Using The Most Relevant Spatial-Temporal Relations
This paper proposes an adaptive deep learning model called spatial-temporal deep neural network (ST-DNN) to forecast air quality up to 48 hours in the future. The model uses historical data from multiple monitoring locations to extract spatial-temporal relationships using convolutional neural networks and long short-term memory. It considers factors like PM2.5, temperature, wind and elevation to predict pollution propagation between locations over time.
Detailed Information
| Author: | ['bella'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 14 |
| Language: | English |
| Format: | |
| Price: | FREE |
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