Machine learning algorithms to forecast air quality: a survey
Air pollution is a risk factor for many diseases that can lead to death. Therefore, it is
important to develop forecasting mechanisms that can be used by the authorities, so that …
important to develop forecasting mechanisms that can be used by the authorities, so that …
Spatio-temporal air quality analysis and PM2. 5 prediction over Hyderabad City, India using artificial intelligence techniques
Air pollution is one of the most serious environmental issues faced by humans, and it affects
the quality of life in cities. PM 2.5 forecasting models can be used to create strategies for …
the quality of life in cities. PM 2.5 forecasting models can be used to create strategies for …
A hybrid deep learning model for regional O3 and NO2 concentrations prediction based on spatiotemporal dependencies in air quality monitoring network
Short-term prediction of urban air quality is critical to pollution management and public
health. However, existing studies have failed to make full use of the spatiotemporal …
health. However, existing studies have failed to make full use of the spatiotemporal …
Dynamic graph convolution neural network based on spatial-temporal correlation for air quality prediction
A Dun, Y Yang, F Lei - Ecological Informatics, 2022 - Elsevier
Air pollution is a serious threat to both the ecological environment and the physical health of
individuals. Therefore, accurate air quality prediction is urgent and necessary for pollution …
individuals. Therefore, accurate air quality prediction is urgent and necessary for pollution …
Indoor air quality pollutants predicting approach using unified labelling process-based multi-criteria decision making and machine learning techniques
NS Baqer, AS Albahri, HA Mohammed… - Telecommunication …, 2022 - Springer
Indoor air quality (IAQ) refers to the conditions found within buildings that can impact
respiratory health. Good IAQ conditions for hospital facilities are essential, especially for …
respiratory health. Good IAQ conditions for hospital facilities are essential, especially for …
Analysis of deep learning approaches for air pollution prediction
V Gugnani, RK Singh - Multimedia Tools and Applications, 2022 - Springer
Due to the urban and industrial growth, many evolving countries suffer from excessive air
pollution. The growing concern about air pollution has been raised by the government and …
pollution. The growing concern about air pollution has been raised by the government and …
An enhanced gated recurrent unit with auto-encoder for solving text classification problems
Classification has become an important task for automatically categorizing documents
based on their respective group. The purpose of classification is to assign the pre-specified …
based on their respective group. The purpose of classification is to assign the pre-specified …
[HTML][HTML] Enhancing Air Quality Prediction with an Adaptive PSO-Optimized CNN-Bi-LSTM Model
X Zhu, F Zou, S Li - Applied Sciences, 2024 - mdpi.com
Effective air quality prediction models are crucial for the timely prevention and control of air
pollution. However, previous models often fail to fully consider air quality's temporal and …
pollution. However, previous models often fail to fully consider air quality's temporal and …
Recent trends in air quality prediction: An artificial intelligence perspective
Many countries are suffering from air pollution due to imbalanced urbanization, unregulated
increase in transportation, and inorganic industrialization. Air pollution directly affects the …
increase in transportation, and inorganic industrialization. Air pollution directly affects the …
Modelos de Predicción de Radiación Solar y Temperatura Ambiente mediante Redes Neuronales Recurrentes
RES El objetivo de este estudio es comparar dos arquitecturas de redes neuronales
recurrentes de Elman y Jordan (RNRE y RNRJ), enfocadas en predicción de dos días de …
recurrentes de Elman y Jordan (RNRE y RNRJ), enfocadas en predicción de dos días de …