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Forecasting of Beijing PM(2.5) with a hybrid ARIMA model based on integrated AIC and improved GS fixed-order methods and seasonal decomposition
Accurate particulate matter 2.5 (PM(2.5)) prediction plays a crucial role in the accurate management of air pollution and prevention of respiratory diseases. However, PM(2.5), as a nonlinear time series with great volatility, is difficult to achieve accurate prediction. In this paper, a hybrid autor...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9800338/ https://www.ncbi.nlm.nih.gov/pubmed/36590504 http://dx.doi.org/10.1016/j.heliyon.2022.e12239 |