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 on emerging artificial intelligence (AI) techniques for air pollution forecasting: Fundamentals, application and performance
Accurate air quality forecasting is critical for systematic pollution control as well as public
health and wellness. Most of the traditional forecasting techniques have shown inconsistent …
health and wellness. Most of the traditional forecasting techniques have shown inconsistent …
Federated learning in the sky: Aerial-ground air quality sensing framework with UAV swarms
Due to air quality significantly affects human health, it is becoming increasingly important to
accurately and timely predict the air quality index (AQI). To this end, this article proposes a …
accurately and timely predict the air quality index (AQI). To this end, this article proposes a …
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 …
Deep learning for air quality forecasts: a review
Q Liao, M Zhu, L Wu, X Pan, X Tang, Z Wang - Current Pollution Reports, 2020 - Springer
Air pollution is one of major environmental issues in the twenty-first century due to global
industrialization and urbanization. Its mitigation necessitates accurate air quality forecasts …
industrialization and urbanization. Its mitigation necessitates accurate air quality forecasts …
Improved ANFIS model for forecasting Wuhan City Air Quality and analysis COVID-19 lockdown impacts on air quality
In this study, we propose an improved version of the adaptive neuro-fuzzy inference system
(ANFIS) for forecasting the air quality index in Wuhan City, China. We propose a hybrid …
(ANFIS) for forecasting the air quality index in Wuhan City, China. We propose a hybrid …
RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach
X Pan, HB Shen - BMC bioinformatics, 2017 - Springer
Background RNAs play key roles in cells through the interactions with proteins known as the
RNA-binding proteins (RBP) and their binding motifs enable crucial understanding of the …
RNA-binding proteins (RBP) and their binding motifs enable crucial understanding of the …
Air pollution forecasting based on attention‐based LSTM neural network and ensemble learning
DR Liu, SJ Lee, Y Huang, CJ Chiu - Expert Systems, 2020 - Wiley Online Library
With air pollution having become a global concern, scientists are committed to working on its
amelioration. In the field of air pollution prediction, there have been good results in …
amelioration. In the field of air pollution prediction, there have been good results in …
A deep learning and image-based model for air quality estimation
Q Zhang, F Fu, R Tian - Science of The Total Environment, 2020 - Elsevier
The serious threat of air pollution to human health makes air quality a focus of public
attention, and effective, timely air quality monitoring is critical to pollution control and human …
attention, and effective, timely air quality monitoring is critical to pollution control and human …
Third-eye: A mobilephone-enabled crowdsensing system for air quality monitoring
Air pollution has raised people's public health concerns in major cities, especially for
Particulate Matter under 2.5 μm (PM2. 5) due to its significant impact on human respiratory …
Particulate Matter under 2.5 μm (PM2. 5) due to its significant impact on human respiratory …