Deepairnet: Applying recurrent networks for air quality prediction
V Athira, P Geetha, R Vinayakumar… - Procedia computer science, 2018 - Elsevier
With the quick advancement of urbanization and industrialization, air pollution has become a
serious issue in developing countries. Governments and natives have raised their …
serious issue in developing countries. Governments and natives have raised their …
[PDF][PDF] Air quality prediction in Visakhapatnam with LSTM based recurrent neural networks
The research activity considered in this paper concerns about efficient approach for
modeling and prediction of air quality. Poor air quality is an environmental hazard that has …
modeling and prediction of air quality. Poor air quality is an environmental hazard that has …
Genetic algorithm-based hyperparameter optimization of deep learning models for PM2.5 time-series prediction
C Erden - International Journal of Environmental Science and …, 2023 - Springer
Since air pollution negatively affects human health and causes serious diseases, accurate
air pollution prediction is essential regarding environmental sustainability. Although …
air pollution prediction is essential regarding environmental sustainability. Although …
[PDF][PDF] Air pollution modelling with deep learning: a review
Air pollution is one of the fundamental environmental problems of the industrialized world
due to its adverse effects on all organisms. Several institutions warn that there exist serious …
due to its adverse effects on all organisms. Several institutions warn that there exist serious …
A deep learning approach for forecasting air pollution in South Korea using LSTM
Tackling air pollution is an imperative problem in South Korea, especially in urban areas,
over the last few years. More specially, South Korea has joined the ranks of the world's most …
over the last few years. More specially, South Korea has joined the ranks of the world's most …
Air pollution concentration forecast method based on the deep ensemble neural network
The global environment has become more polluted due to the rapid development of
industrial technology. However, the existing machine learning prediction methods of air …
industrial technology. However, the existing machine learning prediction methods of air …
[HTML][HTML] Short-Term Prediction of PM2.5 Using LSTM Deep Learning Methods
This paper implements deep learning methods of recurrent neural networks and short-term
memory models. Two kinds of time-series data were used: air pollutant factors, such as O3 …
memory models. Two kinds of time-series data were used: air pollutant factors, such as O3 …
Predicting concentration levels of air pollutants by transfer learning and recurrent neural network
Air pollution (AP) poses a great threat to human health, and people are paying more
attention than ever to its prediction. Accurate prediction of AP helps people to plan for their …
attention than ever to its prediction. Accurate prediction of AP helps people to plan for their …
Dynamically pre-trained deep recurrent neural networks using environmental monitoring data for predicting PM2.5
Abstract Fine particulate matter (PM 2.5) has a considerable impact on human health, the
environment and climate change. It is estimated that with better predictions, US $9 billion …
environment and climate change. It is estimated that with better predictions, US $9 billion …
A novel deep learning approach to predict air quality index
In accordance with the World Health Organization's instruction, the air quality in Bangladesh
is considered perilous. A productive and precise air quality index (AQI) is a must and one of …
is considered perilous. A productive and precise air quality index (AQI) is a must and one of …