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...

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Detalles Bibliográficos
Autores principales: Zhao, Lingxiao, Li, Zhiyang, Qu, Leilei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Research Article
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

Internet

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

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