Deep learning for air quality forecasts: a review
Q Liao, M Zhu, L Wu, X Pan, X Tang, Z Wang - Current Pollution Reports, 2020 - Springer
Air pollution is one of major environmental issues in the twenty-first century due to global
industrialization and urbanization. Its mitigation necessitates accurate air quality forecasts …
industrialization and urbanization. Its mitigation necessitates accurate air quality forecasts …
Deep learning for air pollutant concentration prediction: A review
Air pollution has become one of the critical environmental problem in the 21st century and
has attracted worldwide attentions. To mitigate it, many researchers have investigated the …
has attracted worldwide attentions. To mitigate it, many researchers have investigated the …
Deep air quality forecasting using hybrid deep learning framework
Air quality forecasting has been regarded as the key problem of air pollution early warning
and control management. In this article, we propose a novel deep learning model for air …
and control management. In this article, we propose a novel deep learning model for air …
Ensemble multifeatured deep learning models for air quality forecasting
CY Lin, YS Chang, S Abimannan - Atmospheric Pollution Research, 2021 - Elsevier
As air pollution becomes increasingly serious, accurate forecasting of air quality has
become an important issue. Many studies related to machine learning and deep learning …
become an important issue. Many studies related to machine learning and deep learning …
A systematic literature review of deep learning neural network for time series air quality forecasting
Rapid progress of industrial development, urbanization and traffic has caused air quality
reduction that negatively affects human health and environmental sustainability, especially …
reduction that negatively affects human health and environmental sustainability, especially …
Improving air quality prediction accuracy at larger temporal resolutions using deep learning and transfer learning techniques
As air pollution becomes more and more severe, air quality prediction has become an
important approach for air pollution management and prevention. In recent years, a number …
important approach for air pollution management and prevention. In recent years, a number …
A deep learning approach for forecasting air pollution in South Korea using LSTM
Tackling air pollution is an imperative problem in South Korea, especially in urban areas,
over the last few years. More specially, South Korea has joined the ranks of the world's most …
over the last few years. More specially, South Korea has joined the ranks of the world's most …
A hybrid deep learning framework for urban air quality forecasting
A Aggarwal, D Toshniwal - Journal of Cleaner Production, 2021 - Elsevier
Deep learning models address air quality forecasting problems far more effectively and
efficiently than the traditional machine learning models. Specifically, Long Short-Term …
efficiently than the traditional machine learning models. Specifically, Long Short-Term …
Integrated multiple directed attention-based deep learning for improved air pollution forecasting
In recent years, human health across the world is becoming concerned by a constant threat
of air pollution, which causes many chronic diseases and premature mortalities. Poor air …
of air pollution, which causes many chronic diseases and premature mortalities. Poor air …
[HTML][HTML] Attention-based distributed deep learning model for air quality forecasting
AG Mengara Mengara, E Park, J Jang, Y Yoo - Sustainability, 2022 - mdpi.com
Air quality forecasting has become an essential factor in facilitating sustainable development
worldwide. Several countries have implemented monitoring stations to collect air pollution …
worldwide. Several countries have implemented monitoring stations to collect air pollution …