Air quality prediction using CNN+LSTM-based hybrid deep learning architecture.

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作者： Aysenur,Gilik ^[1] ; Arif Selcuk,Ogrenci ^[2] ; Atilla,Ozmen ^[2]

作者单位： Electrical & Electronics Engineering Department, Kadir Has University, Fatih, Istanbul, Turkey. aysenur.gilik@khas.edu.tr. ^[1] Electrical & Electronics Engineering Department, Kadir Has University, Fatih, Istanbul, Turkey. ^[2]

关键词 Air pollution Convolutional neural network Deep learning Long short-term memory Prediction Transfer learning

主题词空气污染物(Air Pollutants);空气污染(Air Pollution);环境监测(Environmental Monitoring);颗粒物(Particulate Matter)

DOI 10.1007/s11356-021-16227-w

PMID 34554404

发布时间 2022-01-31

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Environmental science and pollution research international

2022年29卷8期

11920-11938页

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Air quality prediction using CNN+LSTM-based hybrid deep learning architecture.

Environmental science and pollution research international

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Environmental science and pollution research international

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Air quality prediction using CNN+LSTM-based hybrid deep learning architecture.

Environmental science and pollution research international

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Environmental science and pollution research international

相关期刊

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