Hybrid framework for improved PM2.5 prediction based on seasonal-trend decomposition and tailored component processing
Abstract Precise prediction of PM2.5 concentrations is crucial for effective environmental management and the safeguarding of public health. However, accurately forecasting PM2.5 levels presents significant challenges due to the complex, non-linear, and non-stationary characteristics inherent in the...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-04597-x |
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