Air Pollution Forecasting Using a Deep Learning Model Based on 1D Convnets and Bidirectional GRU

Air Pollution Forecasting Using a Deep Learning Model Based on 1D Convnets and Bidirectional GRU

Air pollution forecasting can provide reliable information about the future pollution situation, which is useful for an efficient operation of air pollution control and helps to plan for prevention. Dynamics of air pollution are usually reflected by various factors, such as the temperature, humidity...

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Bibliographic Details
Main Authors: Qing Tao, Fang Liu, Yong Li, Denis Sidorov
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Air pollution forecasting
deep learning
1D convolutional neural networks
bidirectional gated recurrent unit
Online Access:https://ieeexplore.ieee.org/document/8732985/

Internet

https://ieeexplore.ieee.org/document/8732985/

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