Computational deep air quality prediction techniques: a systematic review
The escalating population and rapid industrialization have led to a significant rise in
environmental pollution, particularly air pollution. This has detrimental effects on both the …
environmental pollution, particularly air pollution. This has detrimental effects on both the …
State-of-art in modelling particulate matter (PM) concentration: a scoping review of aims and methods
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 …
accurate assessment of population exposure would require a continuous distribution of …
Prediction of Monthly PM2.5 Concentration in Liaocheng in China Employing Artificial Neural Network
Z He, Q Guo, Z Wang, X Li - Atmosphere, 2022 - mdpi.com
Fine particulate matter (PM2. 5) affects climate change and human health. Therefore, the
prediction of PM2. 5 level is particularly important for regulatory planning. The main …
prediction of PM2. 5 level is particularly important for regulatory planning. The main …
On the opportunities of green computing: A survey
Artificial Intelligence (AI) has achieved significant advancements in technology and research
with the development over several decades, and is widely used in many areas including …
with the development over several decades, and is widely used in many areas including …
[HTML][HTML] Analysis and Prediction of Atmospheric Environmental Quality Based on the Autoregressive Integrated Moving Average Model (ARIMA Model) in Hunan …
W Gao, T Xiao, L Zou, H Li, S Gu - Sustainability, 2024 - mdpi.com
Based on the panel data of atmospheric environmental pollution in Hunan Province from
2016 to 2023, the autoregressive integrated moving average model (ARIMA) is introduced to …
2016 to 2023, the autoregressive integrated moving average model (ARIMA) is introduced to …
Adaptive scalable spatio-temporal graph convolutional network for PM2. 5 prediction
Q Ni, Y Wang, J Yuan - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
PM2. 5 Prediction is a complex task of large-scale spatio-temporal analysis, which not only
needs comprehension of static geospatial knowledge and relative features but also needs to …
needs comprehension of static geospatial knowledge and relative features but also needs to …
Impact of Green Energy Transportation Systems on Urban Air Quality: A Predictive Analysis Using Spatiotemporal Deep Learning Techniques
Transitioning to green energy transport systems, notably electric vehicles, is crucial to both
combat climate change and enhance urban air quality in developing nations. Urban air …
combat climate change and enhance urban air quality in developing nations. Urban air …
Spatial mapping of land susceptibility to dust emissions using optimization of attentive Interpretable Tabular Learning (TabNet) model
SV Razavi-Termeh, A Sadeghi-Niaraki… - Journal of …, 2024 - Elsevier
Dust pollution poses significant risks to human health, air quality, and food safety,
necessitating the identification of dust occurrence and the development of dust susceptibility …
necessitating the identification of dust occurrence and the development of dust susceptibility …
Dust detection and susceptibility mapping by aiding satellite imagery time series and integration of ensemble machine learning with evolutionary algorithms
To mitigate the impact of dust on human health and the environment, it is crucial to create a
model and map that identifies the areas susceptible to dust. The present study focused on …
model and map that identifies the areas susceptible to dust. The present study focused on …
Harnessing deep learning for forecasting fire-burning locations and unveiling emissions
Climate change and human activity have increased fires in India. Fine particulate matter (PM
2.5) is released into the atmosphere by stubble burning in Punjab and Haryana and forest …
2.5) is released into the atmosphere by stubble burning in Punjab and Haryana and forest …