Application of CNN-LSTM Algorithm for PM_2.5 Concentration Forecasting in the Beijing-Tianjin-Hebei Metropolitan Area

Prolonged exposure to high concentrations of suspended particulate matter (SPM), especially aerodynamic fine particulate matter that is ≤2.5 μm in diameter (PM_2.5), can cause serious harm to human health and life via the induction of respiratory diseases and lung cancer. Therefore, accura...

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Bibliografiset tiedot

Päätekijät:	Yuxuan Su, Junyu Li, Lilong Liu, Xi Guo, Liangke Huang, Mingyun Hu
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2023-09-01
Sarja:	Atmosphere
Aiheet:	PM<sub>2.5</sub> machine learning Convolutional Neural Network LSTM time series forecasting Precipitable Water Vapor Beijing-Tianjin-Hebei metropolitan area
Linkit:	https://www.mdpi.com/2073-4433/14/9/1392
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