Multi-hour and multi-site air quality index forecasting in Beijing using CNN, LSTM, CNN-LSTM, and spatiotemporal clustering
R Yan, J Liao, J Yang, W Sun, M Nong, F Li - Expert Systems with …, 2021 - Elsevier
Effective air quality forecasting models are helpful for timely prevention and control of air
pollution. However, the spatiotemporal distribution characteristics of air quality have not …
pollution. However, the spatiotemporal distribution characteristics of air quality have not …
PM2. 5 concentrations forecasting in Beijing through deep learning with different inputs, model structures and forecast time
J Yang, R Yan, M Nong, J Liao, F Li, W Sun - Atmospheric Pollution …, 2021 - Elsevier
Timely and accurate air quality forecasting is of great significance for prevention and
mitigation of air pollution. However, most of the previous forecasting models only considered …
mitigation of air pollution. However, most of the previous forecasting models only considered …
Air quality index forecast in Beijing based on CNN-LSTM multi-model
J Zhang, S Li - Chemosphere, 2022 - Elsevier
Accurate predicting the air quality trend can provide a theoretical basis for environmental
protection management and decision-making. This study proposed the convolutional neural …
protection management and decision-making. This study proposed the convolutional neural …
Multi-step ahead forecasting of regional air quality using spatial-temporal deep neural networks: a case study of Huaihai Economic Zone
Highlights•A novel artificial intelligence methodology for multi-step ahead forecasting and
analysis of air quality.•Inclusion of spatial information improves regional air quality …
analysis of air quality.•Inclusion of spatial information improves regional air quality …
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 …
Explore a deep learning multi-output neural network for regional multi-step-ahead air quality forecasts
Timely regional air quality forecasting in a city is crucial and beneficial for supporting
environmental management decisions as well as averting serious accidents caused by air …
environmental management decisions as well as averting serious accidents caused by air …
Forecasting air pollutant concentration using a novel spatiotemporal deep learning model based on clustering, feature selection and empirical wavelet transform
J Kim, X Wang, C Kang, J Yu, P Li - Science of the Total Environment, 2021 - Elsevier
Accurate forecasting of air pollutant concentration is of great importance since it is an
essential part of the early warning system. However, it still remains a challenge due to the …
essential part of the early warning system. However, it still remains a challenge due to the …
Multi-directional temporal convolutional artificial neural network for PM2. 5 forecasting with missing values: A deep learning approach
Data imputation and forecasting are the major research areas in environmental data
engineering. Solving those critical issues has an immense impact on air pollution …
engineering. Solving those critical issues has an immense impact on air pollution …
[HTML][HTML] Multi-output machine learning model for regional air pollution forecasting in Ho Chi Minh City, Vietnam
R Rakholia, Q Le, BQ Ho, K Vu, RS Carbajo - Environment international, 2023 - Elsevier
Air pollution concentrations in Ho Chi Minh City (HCMC) have been found to surpass the
WHO standard, which has become a very serious problem affecting human health and the …
WHO standard, which has become a very serious problem affecting human health and the …
Real time image-based air quality forecasts using a 3D-CNN approach with an attention mechanism
This study presented an image-based deep learning method to improve the recognition of
air quality from images and produce accurate multiple horizon forecasts. The proposed …
air quality from images and produce accurate multiple horizon forecasts. The proposed …