Development of PM<sub>2.5</sub> Forecast Model Combining ConvLSTM and DNN in Seoul

Development of PM<sub>2.5</sub> Forecast Model Combining ConvLSTM and DNN in Seoul

Accurate prediction of PM<sub>2.5</sub> concentrations is essential for public health management, especially in areas affected by long-range pollutant transport. This study presents a hybrid model combining convolutional long short-term memory (ConvLSTM) and deep neural networks (DNNs) t...

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Bibliographic Details
Main Authors: Ji-Seok Koo, Kyung-Hui Wang, Hui-Young Yun, Hee-Yong Kwon, Youn-Seo Koo
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Atmosphere
Subjects:
PM<sub>2.5</sub>
forecast
convLSTM
DNN
hybrid model
Online Access:https://www.mdpi.com/2073-4433/15/11/1276
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