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 …
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 …
An integrated 3D CNN-GRU deep learning method for short-term prediction of PM2. 5 concentration in urban environment
This study proposes a new model for the spatiotemporal prediction of PM 2.5 concentration
at hourly and daily time intervals. It has been constructed on a combination of three …
at hourly and daily time intervals. It has been constructed on a combination of three …
[HTML][HTML] Predicting the number of dusty days around the desert wetlands in southeastern Iran using feature selection and machine learning techniques
In the past decades, some desert wetlands have become critical regions for dust production
in the arid and semi-arid regions of the world. Accurate prediction of the number of dusty …
in the arid and semi-arid regions of the world. Accurate prediction of the number of dusty …
Air quality monitoring based on chemical and meteorological drivers: Application of a novel data filtering-based hybridized deep learning model
Particulate matter (PM) or particle pollution include the tiny particles of dust and fly ash
particles are expelled from coal-burning power plants. Coal combustion is an extremely …
particles are expelled from coal-burning power plants. Coal combustion is an extremely …
A hybrid spatiotemporal deep model based on CNN and LSTM for air pollution prediction
S Tsokov, M Lazarova, A Aleksieva-Petrova - Sustainability, 2022 - mdpi.com
Nowadays, air pollution is an important problem with negative impacts on human health and
on the environment. The air pollution forecast can provide important information to all …
on the environment. The air pollution forecast can provide important information to all …
Data-driven predictive modeling of PM2.5 concentrations using machine learning and deep learning techniques: a case study of Delhi, India
The present study intends to use machine learning (ML) and deep learning (DL) models to
forecast PM2. 5 concentration at a location in Delhi. For this purpose, multi-layer feed …
forecast PM2. 5 concentration at a location in Delhi. For this purpose, multi-layer feed …
Machine learning methods to forecast the concentration of PM10 in Lublin, Poland
J Kujawska, M Kulisz, P Oleszczuk, W Cel - Energies, 2022 - mdpi.com
Air pollution has a major impact on human health, especially in cities, and elevated
concentrations of PMx are responsible for a large number of premature deaths each year …
concentrations of PMx are responsible for a large number of premature deaths each year …
On the predictability of short-lived particulate matter around a cement plant in Kerman, Iran: machine learning analysis
One of the greatest environmental risks in the cement industry is particulate matter emission
(ie, PM2. 5 and PM10). This paper aims to develop descriptive-analytical solutions for …
(ie, PM2. 5 and PM10). This paper aims to develop descriptive-analytical solutions for …
A comparison of machine learning methods to forecast tropospheric ozone levels in Delhi
EK Juarez, MR Petersen - Atmosphere, 2021 - mdpi.com
Ground-level ozone is a pollutant that is harmful to urban populations, particularly in
developing countries where it is present in significant quantities. It greatly increases the risk …
developing countries where it is present in significant quantities. It greatly increases the risk …