A comparison of machine learning methods for ozone pollution prediction

Q Pan, F Harrou, Y Sun - Journal of Big Data, 2023 - Springer
Precise and efficient ozone (O 3) concentration prediction is crucial for weather monitoring
and environmental policymaking due to the harmful effects of high O 3 pollution levels on …

Systematic Review of Air Pollution in Morocco: Status, Impacts, and Future Directions

I Sekmoudi, M Tanarhte, H Bouzghiba… - Advanced …, 2024 - Wiley Online Library
Despite the recognition of the importance of air pollution in Morocco, current scientific
studies are predominantly descriptive and limited. This systematic review aims to provide a …

Prediction of ozone hourly concentrations based on machine learning technology

D Li, X Ren - Sustainability, 2022 - mdpi.com
To optimize the accuracy of ozone (O3) concentration prediction, this paper proposes a
combined prediction model of O3 hourly concentration, FC-LsOA-KELM, which integrates …

Ozone concentration at various heights near the surface layer in Shenyang, Northeast China

L Li, N Liu, L Shen, Z Zhao, H Wang, Y Wang… - Frontiers in …, 2022 - frontiersin.org
Ozone pollution has been growing in the recent decade, becoming a critical urban
environmental issue in China. However, Shenyang's near-surface ozone concentration …

Transformer-Based Model for Multi-Horizon Forecasting Ozone in Marrakech city, Morocco

A Bekkar, B Hssina, S Douzi… - 2023 14th International …, 2023 - ieeexplore.ieee.org
Ozone is a major air pollutant that can cause respiratory problems and other health risks. It is
formed when pollutants from cars, power plants, and other sources react in the presence of …

Prediction of Gas Emission in the Working Face Based on LASSO-WOA-XGBoost

W Song, X Han, J Qi - Atmosphere, 2023 - mdpi.com
In order to improve the prediction accuracy of gas emission in the mining face, a method
combining least absolute value convergence and selection operator (LASSO), whale …

Comparison of 24 h Surface Ozone Forecast for Poland: CAMS Models vs. Simple Statistical Models with Limited Number of Input Parameters

I Pawlak, A Fernandes, J Jarosławski, K Klejnowski… - Atmosphere, 2023 - mdpi.com
Surface ozone is usually measured in national networks, including the monitoring of
gaseous components important for determining air quality and the short-term forecast of …

Prediction of High-ozone Events Using GAM, SMOTE, and Tail Dependence Approaches in Texas (2005–2019)

B Brown-Steiner, X Zhou, MJ Alvarado… - Aerosol and Air Quality …, 2021 - aaqr.org
We test three methods for ozone prediction in the El Paso (ELP) and Houston-Galveston-
Brazoria (HGB) regions of Texas from 2005–2019:(1) a Generalized Additive Model (GAMs) …

k-nearest neighbors prediction and classification for spatial data

MS Ahmed, M N'diaye, MK Attouch… - arXiv preprint arXiv …, 2018 - arxiv.org
This paper proposes a spatial k-nearest neighbor method for nonparametric prediction of
real-valued spatial data and supervised classification for categorical spatial data. The …

A Comparative Study Between NARX and LSTM Models in Predicting Ozone Concentrations: Case of Agadir City (Morocco)

A Adnane, A Ajdour, R Leghrib, J Chaoufi… - AI and IoT for …, 2022 - Springer
It is well known that air pollution has become a significant global environmental problem
causing numerous chronic diseases to humans. Many countries worldwide, including …