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 …
Advances in air quality research–current and emerging challenges
This review provides a community's perspective on air quality research focusing mainly on
developments over the past decade. The article provides perspectives on current and future …
developments over the past decade. The article provides perspectives on current and future …
[HTML][HTML] The MERRA-2 aerosol reanalysis, 1980 onward. Part I: System description and data assimilation evaluation
The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part I: System Description and Data
Assimilation Evaluation in: Journal of Climate Volume 30 Issue 17 (2017) Jump to Content …
Assimilation Evaluation in: Journal of Climate Volume 30 Issue 17 (2017) Jump to Content …
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 …
Deep distributed fusion network for air quality prediction
Accompanying the rapid urbanization, many develo** countries are suffering from serious
air pollution problem. The demand for predicting future air quality is becoming increasingly …
air pollution problem. The demand for predicting future air quality is becoming increasingly …
Air pollution forecasts: An overview
L Bai, J Wang, X Ma, H Lu - … journal of environmental research and public …, 2018 - mdpi.com
Air pollution is defined as a phenomenon harmful to the ecological system and the normal
conditions of human existence and development when some substances in the atmosphere …
conditions of human existence and development when some substances in the atmosphere …
[HTML][HTML] Artificial neural networks forecasting of PM2. 5 pollution using air mass trajectory based geographic model and wavelet transformation
X Feng, Q Li, Y Zhu, J Hou, L **, J Wang - Atmospheric Environment, 2015 - Elsevier
In the paper a novel hybrid model combining air mass trajectory analysis and wavelet
transformation to improve the artificial neural network (ANN) forecast accuracy of daily …
transformation to improve the artificial neural network (ANN) forecast accuracy of daily …
Forecasting fine-grained air quality based on big data
In this paper, we forecast the reading of an air quality monitoring station over the next 48
hours, using a data-driven method that considers current meteorological data, weather …
hours, using a data-driven method that considers current meteorological data, weather …
Intelligent modeling strategies for forecasting air quality time series: A review
In recent years, the deterioration of air quality, the frequent events of the air contaminants,
and the health impacts from that have caused continuous attention by the government and …
and the health impacts from that have caused continuous attention by the government and …
Machine learning approaches for outdoor air quality modelling: A systematic review
Current studies show that traditional deterministic models tend to struggle to capture the non-
linear relationship between the concentration of air pollutants and their sources of emission …
linear relationship between the concentration of air pollutants and their sources of emission …