The application of strategy based on LSTM for the short-term prediction of PM2. 5 in city
MD Lin, PY Liu, CW Huang, YH Lin - Science of The Total Environment, 2024 - Elsevier
Many cities have long suffered from the events of fine particulate matter (PM 2.5) pollutions.
The Taiwanese Government has long strived to accurately predict the short-term hourly …
The Taiwanese Government has long strived to accurately predict the short-term hourly …
Long short-term memory deep neural network model for PM2. 5 forecasting in the Bangkok urban area
K Thaweephol, N Wiwatwattana - 2019 17th International …, 2019 - ieeexplore.ieee.org
Accurately forecasting fine particulate matter of less than a 2.5 micrometer diameter (PM2. 5)
concentration levels is important to better manage the air pollution situation and to give …
concentration levels is important to better manage the air pollution situation and to give …
A long short-term memory-based hybrid model optimized using a genetic algorithm for particulate matter 2.5 prediction
Abstract Beijing, Shanghai, Singapore, and London are regions with high population density
and industrial activities. In this sense, accurate prediction of the rate of particulate matter 2.5 …
and industrial activities. In this sense, accurate prediction of the rate of particulate matter 2.5 …
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 …
Forecasting hourly PM2. 5 concentration with an optimized LSTM model
HD Tran, HY Huang, JY Yu, SH Wang - Atmospheric Environment, 2023 - Elsevier
Abstract Machine learning has become a powerful tool in air quality assessment which can
provide timely and predictable information, alert the public, and take timely measures to …
provide timely and predictable information, alert the public, and take timely measures to …
Urban PM2.5 Concentration Prediction via Attention-Based CNN–LSTM
Urban particulate matter forecasting is regarded as an essential issue for early warning and
control management of air pollution, especially fine particulate matter (PM2. 5). However …
control management of air pollution, especially fine particulate matter (PM2. 5). However …
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 …
Spatiotemporal prediction of PM2. 5 concentrations at different time granularities using IDW-BLSTM
As air pollution becomes an increasing concern globally, governments, and research
institutions have attached great importance to air quality prediction to help give early …
institutions have attached great importance to air quality prediction to help give early …
Prediction of PM2. 5 concentration in urban agglomeration of China by hybrid network model
S Wu, H Li - Journal of Cleaner Production, 2022 - Elsevier
The urban agglomeration area is a heavy disaster area of PM2. 5 pollution, and the problem
of PM2. 5 pollution seriously affects the natural environment and public health. Accurate …
of PM2. 5 pollution seriously affects the natural environment and public health. Accurate …
RCL-Learning: ResNet and convolutional long short-term memory-based spatiotemporal air pollutant concentration prediction model
Predicting the concentration of air pollutants is an effective method for preventing pollution
incidents by providing an early warning of harmful substances in the air. Accurate prediction …
incidents by providing an early warning of harmful substances in the air. Accurate prediction …