Time Series Analysis: Application of LSTM model in predicting PM 2.5 concentration in Beijing
Air pollution forecasting for public health and policy-making has a critical importance, this paper employs a Long Short-Term Memory (LSTM) model to perform in-depth prediction of PM2.5 concentrations measured at the U.S. Embassy in Beijing, outperforming regular forecasting approaches. In the LSTM...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
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| Series: | ITM Web of Conferences |
| Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2025/01/itmconf_dai2024_04022.pdf |
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