Deep learning methods for atmospheric PM2. 5 prediction: A comparative study of transformer and CNN-LSTM-attention
B Cui, M Liu, S Li, Z Jin, Y Zeng, X Lin - Atmospheric Pollution Research, 2023 - Elsevier
A transformer-based method was firstly developed to predict the hourly PM 2.5 concentration
at 12 monitoring stations in Beijing. Convolutional neural network-long short-term memory …
at 12 monitoring stations in Beijing. Convolutional neural network-long short-term memory …
Deep Learning-Based PM2.5 Long Time-Series Prediction by Fusing Multisource Data—A Case Study of Beijing
M Niu, Y Zhang, Z Ren - Atmosphere, 2023 - mdpi.com
Accurate air quality prediction is of great significance for pollution prevention and disaster
prevention. Effective and reliable prediction models are needed not only for short time …
prevention. Effective and reliable prediction models are needed not only for short time …
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 …
A hybrid CNN-LSTM model for forecasting particulate matter (PM2. 5)
T Li, M Hua, XU Wu - Ieee Access, 2020 - ieeexplore.ieee.org
PM2. 5 is one of the most important pollutants related to air quality, and the increase of its
concentration will aggravate the threat to people's health. Therefore, the prediction of …
concentration will aggravate the threat to people's health. Therefore, the prediction of …
Long-term PM2. 5 concentrations forecasting using CEEMDAN and deep Transformer neural network
Q Zeng, L Wang, S Zhu, Y Gao, X Qiu… - Atmospheric Pollution …, 2023 - Elsevier
Abstract Accurate long-term (6–24 h) prediction of PM 2.5 is critical to human health and
daily life. While deep learning techniques have been extensively used to forecast PM 2.5 …
daily life. While deep learning techniques have been extensively used to forecast PM 2.5 …
Deep learning-based PM2. 5 prediction considering the spatiotemporal correlations: A case study of Beijing, China
U Pak, J Ma, U Ryu, K Ryom, U Juhyok, K Pak… - Science of the Total …, 2020 - Elsevier
Air pollution is one of the serious environmental problems that humankind faces and also a
hot topic in Northeastern Asia. Therefore, the accurate prediction of PM2. 5 (particulate …
hot topic in Northeastern Asia. Therefore, the accurate prediction of PM2. 5 (particulate …
Forecasting hourly PM2. 5 based on deep temporal convolutional neural network and decomposition method
For hourly PM 2.5 concentration prediction, accurately capturing the data patterns of external
factors that affect PM 2.5 concentration changes, and constructing a forecasting model is …
factors that affect PM 2.5 concentration changes, and constructing a forecasting model is …
A novel hybrid ensemble model for hourly PM2. 5 forecasting using multiple neural networks: a case study in China
H Liu, S Dong - Air Quality, Atmosphere & Health, 2020 - Springer
High concentration PM2. 5 may cause serious damage to human health. Accurate PM2. 5
concentration forecasting can provide the public with timely and effective PM2. 5 pollution …
concentration forecasting can provide the public with timely and effective PM2. 5 pollution …
Deep learning coupled model based on TCN-LSTM for particulate matter concentration prediction
Y Ren, S Wang, B Xia - Atmospheric Pollution Research, 2023 - Elsevier
In this study, we combined the Temporal Convolutional Network (TCN) model with the Long
Short-Term Memory (LSTM) network model and applied it to prediction of atmospheric …
Short-Term Memory (LSTM) network model and applied it to prediction of atmospheric …
Prediction of Multi-Site PM2.5 Concentrations in Beijing Using CNN-Bi LSTM with CBAM
D Li, J Liu, Y Zhao - Atmosphere, 2022 - mdpi.com
Air pollution is a growing problem and poses a challenge to people's healthy lives. Accurate
prediction of air pollutant concentrations is considered the key to air pollution warning and …
prediction of air pollutant concentrations is considered the key to air pollution warning and …