Air quality index forecast in Beijing based on CNN-LSTM multi-model

Accurate predicting the air quality trend can provide a theoretical basis for environmental protection management and decision-making. This study proposed the convolutional neural networks—long short-term memory (CNN-LSTM) model, which was proposed to improve the air quality prediction accuracy. Fir...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Chemosphere (Oxford) 2022-12, Vol.308, p.136180-136180, Article 136180
Hauptverfasser:	Zhang, Jiaxuan, Li, Shunyong
Format:	Artikel
Sprache:	eng
Schlagworte:	air quality AQI China CNN-LSTM decision making environmental protection Forecasting LSTM memory neural networks prediction SARIMA time series analysis
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!