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 …
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 …
Deep Learning Estimation of Daily Ground‐Level NO2 Concentrations From Remote Sensing Data
The limited number of nitrogen dioxide (NO2) surface measurements calls for the
development of highly accurate approaches to estimating surface NO2 concentrations. In …
development of highly accurate approaches to estimating surface NO2 concentrations. In …
Using a deep convolutional neural network to predict 2017 ozone concentrations, 24 hours in advance
In this study, we use a deep convolutional neural network (CNN) to develop a model that
predicts ozone concentrations 24 h in advance. We have evaluated the model for 21 …
predicts ozone concentrations 24 h in advance. We have evaluated the model for 21 …
Air quality prediction using CT-LSTM
J Wang, J Li, X Wang, J Wang, M Huang - Neural Computing and …, 2021 - Springer
With the development of industry, air pollution has become a serious problem. It is very
important to create an air quality prediction model with high accuracy and good …
important to create an air quality prediction model with high accuracy and good …
Graph convolutional network–Long short term memory neural network-multi layer perceptron-Gaussian progress regression model: A new deep learning model for …
M Ehteram, AN Ahmed, ZS Khozani… - Atmospheric Pollution …, 2023 - Elsevier
Ozone is one of the most important air pollutants. The high ozone concertation (OZC) affects
the environment and public health. Since OZC depends on the number of different variables …
the environment and public health. Since OZC depends on the number of different variables …
Bias correcting and extending the PM forecast by CMAQ up to 7 days using deep convolutional neural networks
With rising levels of air-pollution, air-quality forecasting has become integral to the
dissemination of human health advisories and the preparation of mitigation strategies. To …
dissemination of human health advisories and the preparation of mitigation strategies. To …
Spatiotemporal variations of air pollutants and ozone prediction using machine learning algorithms in the Beijing-Tianjin-Hebei region from 2014 to 2021
China was seriously affected by air pollution in the past decade, especially for particulate
matter (PM) and emerging ozone pollution recently. In this study, we systematically …
matter (PM) and emerging ozone pollution recently. In this study, we systematically …
A comprehensive study of the COVID-19 impact on PM2. 5 levels over the contiguous United States: A deep learning approach
We investigate the impact of the COVID-19 outbreak on PM 2.5 levels in eleven urban
environments across the United States: Washington DC, New York, Boston, Chicago, Los …
environments across the United States: Washington DC, New York, Boston, Chicago, Los …
Contributions of meteorology to ozone variations: Application of deep learning and the Kolmogorov-Zurbenko filter
B Sadeghi, M Ghahremanloo, S Mousavinezhad… - Environmental …, 2022 - Elsevier
From hourly ozone observations obtained from three regions⸻ Houston, Dallas, and West
Texas⸻ we investigated the contributions of meteorology to changes in surface daily …
Texas⸻ we investigated the contributions of meteorology to changes in surface daily …