A hybrid deep learning network for forecasting air pollutant concentrations

Mao, Yu-Shun; Lee, Shie-Jue; Wu, Chih-Hung; Hou, Chun-Liang; Ouyang, Chen‐Sen; Liu, Chih-Feng

doi:10.1007/s10489-022-04191-y

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Cited by 2 publications

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“…Mao et al. [ 139 ] proposed a hybrid DL model that combines CNN, BiGRU, and a fully connected layer. The advantage of these two approaches is their ability to model both spatial and temporal patterns.…”

Section: Methods Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Deep-learning architecture for PM2.5 concentration prediction: A review

Zhou,

Wang,

Zhu

et al. 2024

Environmental Science and Ecotechnology

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Section: Methods Reviewmentioning

confidence: 99%

“…[ 138 ] 2021 Taiwan, China AE + CNN + GRU D/S/T+1 5.03 3.10 - - Mao et al. [ 139 ] 2022 Taiwan, China CNN + GRU H/S/T+1 4.78 3.56 - 0.89 Kennedy/Simon Bolivar, US D/S/T+1 6.83/6.15 5.29/4.58 - 0.44/0.56 …”

Section: Methods Reviewmentioning

confidence: 99%