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 …
Predicting the quality of air with machine learning approaches: Current research priorities and future perspectives
The spiraling growth of the world's population and unregulated urbanization have resulted in
many environmental problems, including poor quality of air, which is associated with a wide …
many environmental problems, including poor quality of air, which is associated with a wide …
Deep spatio-temporal graph network with self-optimization for air quality prediction
The environment and development are major issues of general concern. After much
suffering from the harm of environmental pollution, human beings began to pay attention to …
suffering from the harm of environmental pollution, human beings began to pay attention to …
Multivariate Time-Series Forecasting: A Review of Deep Learning Methods in Internet of Things Applications to Smart Cities
V Papastefanopoulos, P Linardatos… - Smart Cities, 2023 - mdpi.com
Smart cities are urban areas that utilize digital solutions to enhance the efficiency of
conventional networks and services for sustainable growth, optimized resource …
conventional networks and services for sustainable growth, optimized resource …
Spatiotemporal air pollution forecasting in houston-TX: a case study for ozone using deep graph neural networks
The presence of pollutants in our atmosphere has become one of humanity's greatest
challenges. These pollutants, produced primarily by burning fossil fuels, are detrimental to …
challenges. These pollutants, produced primarily by burning fossil fuels, are detrimental to …
水电机组复杂工况振动信号多尺度清洗
刘燚, 刘伟, 时有松, 周建中, 张勇传 - 水力发电学报, 2022 - slfdxb.cn
水电机组振动监测信号常包含大量异常数据, 严重影响机组健康状态评估与预测. 为此,
本文深入研究机组振动与工况的映射关系, 提出了一种基于高斯混合模型和基于密度的噪点空间 …
本文深入研究机组振动与工况的映射关系, 提出了一种基于高斯混合模型和基于密度的噪点空间 …
[HTML][HTML] A systematic survey of air quality prediction based on deep learning
Z Zhang, S Zhang, C Chen, J Yuan - Alexandria Engineering Journal, 2024 - Elsevier
The impact of air pollution on public health is substantial, and accurate long-term predictions
of air quality are crucial for early warning systems to address this issue. Air quality prediction …
of air quality are crucial for early warning systems to address this issue. Air quality prediction …
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 …
A novel approach for the prediction and analysis of daily concentrations of particulate matter using machine learning
Traditional air quality analysis and prediction methods depend on the statistical and
numerical analyses of historical air quality data with more information related to a specific …
numerical analyses of historical air quality data with more information related to a specific …
Air quality prediction model based on mRMR–RF feature selection and ISSA–LSTM
H Wu, T Yang, H Li, Z Zhou - Scientific Reports, 2023 - nature.com
Severe air pollution poses a significant threat to public safety and human health. Predicting
future air quality conditions is crucial for implementing pollution control measures and …
future air quality conditions is crucial for implementing pollution control measures and …