Prediction of Pollutant Concentration Based on Spatial-Temporal Attention, ResNet and ConvLSTM.

Chen, Cai; Qiu, Agen; Chen, Haoyu; Chen, Yajun; Liu, Xu; Li, Dong

Chen, Cai; Qiu, Agen; Chen, Haoyu; Chen, Yajun; Liu, Xu; Li, Dong.

Afiliación

Chen C; School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 102616, China.
Qiu A; Chinese Academy of Surveying and Mapping, Beijing 100830, China.
Chen H; Chinese Academy of Surveying and Mapping, Beijing 100830, China.
Chen Y; Jiangsu Provincial Surveying and Mapping Engineering Institute, Nanjing 210013, China.
Liu X; China Electronics Standardization Institute, Beijing 100007, China.
Li D; School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 102616, China.

Sensors (Basel) ; 23(21)2023 Oct 31.

Article en En | MEDLINE | ID: mdl-37960562

Palabras clave

ConvLSTM; pollutant concentrations; residual network; spatialtemporal attention

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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