Evaluating traditional versus ensemble machine learning methods for predicting missing data of daily PM10 concentration
The aim of this study was to predict the missing data of PM 10 for the city of Zabol using
various traditional learning methods, Lazy Learning, and Ensemble Learning. In this study …
various traditional learning methods, Lazy Learning, and Ensemble Learning. In this study …
[HTML][HTML] 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 …
Spatial prediction of PM10 concentration using machine learning algorithms in Ankara, Turkey
With the increase in population and industrialization, air pollution has become one of the
global problems nowadays. Therefore, air pollutant parameters should be measured at …
global problems nowadays. Therefore, air pollutant parameters should be measured at …
[HTML][HTML] Classification Prediction of PM10 Concentration Using a Tree-Based Machine Learning Approach
The PM10 prediction has received considerable attention due to its harmful effects on
human health. Machine learning approaches have the potential to predict and classify future …
human health. Machine learning approaches have the potential to predict and classify future …
[PDF][PDF] Assessment of machine learning algorithms in short-term forecasting of pm10 and pm2. 5 concentrations in selected polish agglomerations
Air pollution continues to have a significant impact on Europeans living in urban areas, and
episodes of elevated PMx are responsible for a large number of premature deaths (mostly …
episodes of elevated PMx are responsible for a large number of premature deaths (mostly …
[PDF][PDF] PM2. 5 concentration prediction for air pollution using machine learning algorithms
Air pollution is a phenomenon harmful to both human being existence as well as the
ecological system. It is caused by the excess of some substances above a particular …
ecological system. It is caused by the excess of some substances above a particular …
Boosted Regression Tree (BRT) model for PM10 concentrations prediction in Malaysia
R Norazrin, HA Hamid, AS Yahaya - IOP Conference Series …, 2023 - iopscience.iop.org
Air pollution in urban areas is a highly complex problem, displaying strong seasonality and
dependence on meteorological factors. Urban particulate matter with an aerodynamic …
dependence on meteorological factors. Urban particulate matter with an aerodynamic …
A novel ensemble machine learning method for accurate air quality prediction
M Emeç, M Yurtsever - International Journal of Environmental Science and …, 2024 - Springer
Air pollution continues to be an important problem that causes health issues worldwide.
Factors such as industrial development, increased vehicle traffic, and energy production …
Factors such as industrial development, increased vehicle traffic, and energy production …
[HTML][HTML] A Novel Hybrid Model Combining the Support Vector Machine (SVM) and Boosted Regression Trees (BRT) Technique in Predicting PM10 Concentration
The PM10 concentration is subject to significant changes brought on by both gaseous and
meteorological variables. The aim of this research was to explore the performance of a …
meteorological variables. The aim of this research was to explore the performance of a …
[HTML][HTML] Prediction of PM10 Concentration in Malaysia Using K-Means Clustering and LSTM Hybrid Model
Following the rapid development of various industrial sectors, air pollution frequently occurs
in every corner of the world. As a dominant pollutant in Malaysia, particulate matter PM10 …
in every corner of the world. As a dominant pollutant in Malaysia, particulate matter PM10 …