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 …
Air quality prediction in smart cities using machine learning technologies based on sensor data: a review
The influence of machine learning technologies is rapidly increasing and penetrating almost
in every field, and air pollution prediction is not being excluded from those fields. This paper …
in every field, and air pollution prediction is not being excluded from those fields. This paper …
PM2. 5 concentration forecasting at surface monitoring sites using GRU neural network based on empirical mode decomposition
G Huang, X Li, B Zhang, J Ren - Science of the Total Environment, 2021 - Elsevier
The main component of haze is the particulate matter (PM) 2.5. How to explore the laws of
PM2. 5 concentration changes is the main content of air quality prediction. Combining the …
PM2. 5 concentration changes is the main content of air quality prediction. Combining the …
[HTML][HTML] An LSTM-based aggregated model for air pollution forecasting
During the past few years, severe air-pollution problem has garnered worldwide attention
due to its effect on health and wellbeing of individuals. As a result, the analysis and …
due to its effect on health and wellbeing of individuals. As a result, the analysis and …
Air quality prediction at new stations using spatially transferred bi-directional long short-term memory network
In the last decades, air pollution has been a critical environmental issue, especially in
develo** countries like China. The governments and scholars have spent lots of effort on …
develo** countries like China. The governments and scholars have spent lots of effort on …
A bi-directional missing data imputation scheme based on LSTM and transfer learning for building energy data
Improving the energy efficiency of the buildings is a worldwide hot topic nowadays. To assist
comprehensive analysis and smart management, high-quality historical data records of the …
comprehensive analysis and smart management, high-quality historical data records of the …
Air quality prediction using CNN+ LSTM-based hybrid deep learning architecture
Air pollution prediction based on variables in environmental monitoring data gains further
importance with increasing concerns about climate change and the sustainability of cities …
importance with increasing concerns about climate change and the sustainability of cities …
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 …
Identification of high impact factors of air quality on a national scale using big data and machine learning techniques
To effectively control and prevent air pollution, it is necessary to study the influential factors
of air quality. A number of previous studies have explored the relationships between air …
of air quality. A number of previous studies have explored the relationships between air …
Status of air pollution during COVID-19-induced lockdown in Delhi, India
To monitor the spread of the novel coronavirus (COVID-19), India, during the last week of
March 2020, imposed national restrictions on the movement of its citizens (lockdown) …
March 2020, imposed national restrictions on the movement of its citizens (lockdown) …