A deep learning framework for building energy consumption forecast
Increasing global building energy demand, with the related economic and environmental
impact, upsurges the need for the design of reliable energy demand forecast models. This …
impact, upsurges the need for the design of reliable energy demand forecast models. This …
Deep learning for air pollutant concentration prediction: A review
Air pollution has become one of the critical environmental problem in the 21st century and
has attracted worldwide attentions. To mitigate it, many researchers have investigated the …
has attracted worldwide attentions. To mitigate it, many researchers have investigated the …
A review of artificial neural network models for ambient air pollution prediction
Research activity in the field of air pollution forecasting using artificial neural networks
(ANNs) has increased dramatically in recent years. However, the development of ANN …
(ANNs) has increased dramatically in recent years. However, the development of ANN …
Artificial intelligence technologies for forecasting air pollution and human health: a narrative review
Air pollution is a major issue all over the world because of its impacts on the environment
and human beings. The present review discussed the sources and impacts of pollutants on …
and human beings. The present review discussed the sources and impacts of pollutants on …
Application of wavelet-packet transform driven deep learning method in PM2. 5 concentration prediction: A case study of Qingdao, China
Q Zheng, X Tian, Z Yu, N Jiang, A Elhanashi… - Sustainable Cities and …, 2023 - Elsevier
Air pollution is one of the most serious environmental problems faced by human beings, and
it is also a hot topic in the development of sustainable cities. Accurate PM 2.5 prediction …
it is also a hot topic in the development of sustainable cities. Accurate PM 2.5 prediction …
The forecasting of PM2. 5 using a hybrid model based on wavelet transform and an improved deep learning algorithm
W Qiao, W Tian, Y Tian, Q Yang, Y Wang… - IEEE Access, 2019 - ieeexplore.ieee.org
In recent years, the haze has caused serious troubles to people's lives, with the continuous
increase of PM2. 5 emissions. The accurate prediction of PM2. 5 is very crucial for policy …
increase of PM2. 5 emissions. The accurate prediction of PM2. 5 is very crucial for policy …
Intelligent modeling strategies for forecasting air quality time series: A review
In recent years, the deterioration of air quality, the frequent events of the air contaminants,
and the health impacts from that have caused continuous attention by the government and …
and the health impacts from that have caused continuous attention by the government and …
A systematic literature review of deep learning neural network for time series air quality forecasting
Rapid progress of industrial development, urbanization and traffic has caused air quality
reduction that negatively affects human health and environmental sustainability, especially …
reduction that negatively affects human health and environmental sustainability, especially …
COVID-19 lockdowns and air quality: Evidence from grey spatiotemporal forecasts
This paper proposes a novel grey spatiotemporal model and quantitatively analyzes the
spillover and momentum effects of the COVID-19 lockdown policy on the concentration of …
spillover and momentum effects of the COVID-19 lockdown policy on the concentration of …
Air quality predictions with a semi-supervised bidirectional LSTM neural network
L Zhang, P Liu, L Zhao, G Wang, W Zhang… - Atmospheric Pollution …, 2021 - Elsevier
Efficient and accurate air quality predictions can contribute to public health protection and
policy decision making. Fine particulate matter (PM 2.5) is an important index for measuring …
policy decision making. Fine particulate matter (PM 2.5) is an important index for measuring …