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 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 …
Air pollution modelling with deep learning: a review
Air pollution is one of the fundamental environmental problems of the industrialized world
due to its adverse effects on all organisms. Several institutions warn that there exist serious …
due to its adverse effects on all organisms. Several institutions warn that there exist serious …
Deep learning architecture for air quality predictions
With the rapid development of urbanization and industrialization, many developing countries
are suffering from heavy air pollution. Governments and citizens have expressed increasing …
are suffering from heavy air pollution. Governments and citizens have expressed increasing …
An ensemble learning based hybrid model and framework for air pollution forecasting
As advance of economy and industry, the impact of air pollution has gradually gained
attention. In order to predict air quality, there were many studies that exploited various …
attention. In order to predict air quality, there were many studies that exploited various …
Air pollution concentration forecast method based on the deep ensemble neural network
The global environment has become more polluted due to the rapid development of
industrial technology. However, the existing machine learning prediction methods of air …
industrial technology. However, the existing machine learning prediction methods of air …
Spatiotemporal prediction of PM2. 5 concentrations at different time granularities using IDW-BLSTM
As air pollution becomes an increasing concern globally, governments, and research
institutions have attached great importance to air quality prediction to help give early …
institutions have attached great importance to air quality prediction to help give early …
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 Novel Combined Prediction Scheme Based on CNN and LSTM for Urban PM2.5 Concentration
Urban air pollutant concentration prediction is dealing with a surge of massive
environmental monitoring data and complex changes in air pollutants. This requires effective …
environmental monitoring data and complex changes in air pollutants. This requires effective …
A hybrid deep learning model to forecast particulate matter concentration levels in Seoul, South Korea
G Yang, HM Lee, G Lee - Atmosphere, 2020 - mdpi.com
Both long-and short-term exposure to high concentrations of airborne particulate matter (PM)
severely affect human health. Many countries now regulate PM concentrations. Early …
severely affect human health. Many countries now regulate PM concentrations. Early …