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 …
Machine learning algorithms to forecast air quality: a survey
Air pollution is a risk factor for many diseases that can lead to death. Therefore, it is
important to develop forecasting mechanisms that can be used by the authorities, so that …
important to develop forecasting mechanisms that can be used by the authorities, so that …
[HTML][HTML] A time series forecasting based multi-criteria methodology for air quality prediction
There is a very extensive literature on the design and test of models of environmental
pollution, especially in the atmosphere. Current and recent models, however, are focused on …
pollution, especially in the atmosphere. Current and recent models, however, are focused on …
Predicting the quality of air with machine learning approaches: Current research priorities and future perspectives
The spiraling growth of the world's population and unregulated urbanization have resulted in
many environmental problems, including poor quality of air, which is associated with a wide …
many environmental problems, including poor quality of air, which is associated with a wide …
PM2. 5 forecasting for an urban area based on deep learning and decomposition method
Rapid growth in industrialization and urbanization have resulted in high concentration of air
pollutants in the environment and thus causing severe air pollution. Excessive emission of …
pollutants in the environment and thus causing severe air pollution. Excessive emission of …
Forecasting of fine particulate matter based on LSTM and optimization algorithm
Accurate air pollution forecasting may provide valuable information for urban planning to
maintain environmental sustainability and reduce mortality risk due to health problems. The …
maintain environmental sustainability and reduce mortality risk due to health problems. The …
Ensemble multifeatured deep learning models and applications: A survey
Ensemble multifeatured deep learning methodology has emerged as a powerful approach
to overcome the limitations of single deep learning models in terms of generalization …
to overcome the limitations of single deep learning models in terms of generalization …
Towards federated learning and multi-access edge computing for air quality monitoring: literature review and assessment
Systems for monitoring air quality are essential for reducing the negative consequences of
air pollution, but creating real-time systems encounters several challenges. The accuracy …
air pollution, but creating real-time systems encounters several challenges. The accuracy …
Air quality forecasting with artificial intelligence techniques: A scientometric and content analysis
Artificial intelligence (AI) techniques have substantially changed the research paradigm in
the field of air quality forecasting due to their powerful performance. Considering the …
the field of air quality forecasting due to their powerful performance. Considering the …
Gas turbine availability improvement based on long short-term memory networks using deep learning of their failures data analysis
Practically, a maintenance operation is performed on industrial equipment after scheduled
planning that depends on the average useful life of this equipment (Mean Time Between …
planning that depends on the average useful life of this equipment (Mean Time Between …