[HTML][HTML] Deep-learning architecture for PM2. 5 concentration prediction: A review

S Zhou, W Wang, L Zhu, Q Qiao, Y Kang - Environmental Science and …, 2024 - Elsevier
Accurately predicting the concentration of fine particulate matter (PM 2.5) is crucial for
evaluating air pollution levels and public exposure. Recent advancements have seen a …

Prediction of Hourly PM2.5 and PM10 Concentrations in Chongqing City in China Based on Artificial Neural Network

Q Guo, Z He, Z Wang - Aerosol and Air Quality Research, 2023 - Springer
Accurate prediction of air pollution is a difficult problem to be solved in atmospheric
environment research. An Artificial Neural Network (ANN) is exploited to predict hourly PM2 …

State-of-art in modelling particulate matter (PM) concentration: a sco** review of aims and methods

L Gianquintieri, D Oxoli, EG Caiani… - Environment …, 2024 - Springer
Air pollution is the one of the most significant environmental risks to health worldwide. An
accurate assessment of population exposure would require a continuous distribution of …

Forecasting of fine particulate matter based on LSTM and optimization algorithm

AN Ahmed, LW Ean, MF Chow, MA Malek - Journal of Cleaner …, 2023 - Elsevier
Accurate air pollution forecasting may provide valuable information for urban planning to
maintain environmental sustainability and reduce mortality risk due to health problems. The …

Prediction of developmental toxic effects of fine particulate matter (PM2. 5) water-soluble components via machine learning through observation of PM2. 5 from diverse …

Y Fan, N Sun, S Lv, H Jiang, Z Zhang, J Wang… - Science of The Total …, 2024 - Elsevier
The global health implications of fine particulate matter (PM 2.5) underscore the imperative
need for research into its toxicity and chemical composition. In this study, zebrafish embryos …

Improving PM2.5 prediction in New Delhi using a hybrid extreme learning machine coupled with snake optimization algorithm

A Masood, MM Hameed, A Srivastava, QB Pham… - Scientific Reports, 2023 - nature.com
Abstract Fine particulate matter (PM2. 5) is a significant air pollutant that drives the most
chronic health problems and premature mortality in big metropolitans such as Delhi. In such …

Investigate the effects of urban land use on PM2. 5 concentration: An application of deep learning simulation

L Zhao, M Zhang, S Cheng, Y Fang, S Wang… - Building and …, 2023 - Elsevier
As the fine particulate matter (PM 2.5) polluting seriously threat people's health, exploring its
mitigation strategies has become an urgent issue to be studied. Urban land use, the carrier …

An AQI decomposition ensemble model based on SSA-LSTM using improved AMSSA-VMD decomposition reconstruction technique

K Wang, X Fan, X Yang, Z Zhou - Environmental Research, 2023 - Elsevier
Air quality index (AQI) is a key index for monitoring air pollution and can be used as guide
for ensuring good public health. Accurate AQI prediction allows timely control and …

Variation pattern, influential factors, and prediction models of PM2. 5 concentrations in typical urban functional zones of northeast China

D Han, L Shi, M Wang, T Zhang, X Zhang, B Li… - Science of The Total …, 2024 - Elsevier
This study investigated the spatial and temporal variations of PM2. 5 concentrations in
Harbin, China, under the influence of meteorological parameters and gaseous pollutants …

Improved prediction of hourly PM2. 5 concentrations with a long short-term memory and spatio-temporal causal convolutional network deep learning model

Y Chen, L Huang, X **e, Z Liu, J Hu - Science of The Total Environment, 2024 - Elsevier
Accurate prediction of particulate matter with aerodynamic diameter≤ 2.5 μm (PM 2.5) is
important for environmental management and human health protection. In recent years …