Development of PM_2.5 Forecast Model Combining ConvLSTM and DNN in Seoul

Accurate prediction of PM_2.5 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) to enhance PM...

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書誌詳細

主要な著者:	Ji-Seok Koo, Kyung-Hui Wang, Hui-Young Yun, Hee-Yong Kwon, Youn-Seo Koo
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2024-10-01
シリーズ:	Atmosphere
主題:	PM<sub>2.5</sub> forecast convLSTM DNN hybrid model
オンライン･アクセス:	https://www.mdpi.com/2073-4433/15/11/1276
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