Analysis and Prediction of PM2.5 Pollution in Madrid: The Use of Prophet–Long Short-Term Memory Hybrid Models
Particulate matter smaller than 2.5 μm (PM2.5) in Madrid is a critical concern due to its impacts on public health. This study employs advanced methodologies, including the CRISP-DM model and hybrid Prophet–Long Short-Term Memory (LSTM), to analyze historical data from monitoring stations and predic...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
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| Series: | AppliedMath |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-9909/4/4/76 |