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 …
Ground-level ozone prediction using machine learning techniques: A case study in Amman, Jordan
Air pollution is one of the most serious hazards to humans' health nowadays, it is an invisible
killer that takes many human lives every year. There are many pollutants existing in the …
killer that takes many human lives every year. There are many pollutants existing in the …
[PDF][PDF] Predicting ground level ozone in Marrakesh by machine-learning techniques
J Ordieres-Meré, J Ouarzazi, B El Johra, B Gong - J. Environ. Inform, 2020 - academia.edu
This study was undertaken to produce local, short-term, artificial intelligence-based models
that estimate the ozone level with special attention to the relationship between diurnal and …
that estimate the ozone level with special attention to the relationship between diurnal and …
Comprehensive comparison of various machine learning algorithms for short-term ozone concentration prediction
A Yafouz, N AlDahoul, AH Birima, AN Ahmed… - Alexandria Engineering …, 2022 - Elsevier
Ozone (O3) is one of the common air pollutants. An increase in the ozone concentration can
adversely affect public health and the environment such as vegetation and crops. Therefore …
adversely affect public health and the environment such as vegetation and crops. Therefore …
Machine learning versus linear regression modelling approach for accurate ozone concentrations prediction
E Jumin, N Zaini, AN Ahmed, S Abdullah… - Engineering …, 2020 - Taylor & Francis
High level of tropospheric ozone concentration, exceeding allowable level has been
frequently reported in Malaysia. This study proposes accurate model based on Machine …
frequently reported in Malaysia. This study proposes accurate model based on Machine …
Forecasting ground-level ozone concentration levels using machine learning
Ground-level ozone (GLO) has been widely recognized as a critical air pollutant that has the
potential to induce various adverse environmental and health effects. To eliminate its …
potential to induce various adverse environmental and health effects. To eliminate its …
Prediction and examination of seasonal variation of ozone with meteorological parameter through artificial neural network at NEERI, Nagpur, India
The present study focused on seasonal relations and predictions of the ozone (O 3) coupled
with NO 2 and meteorology. Monitoring of ozone concentration throughout year shows an …
with NO 2 and meteorology. Monitoring of ozone concentration throughout year shows an …
Hybrid deep learning model for ozone concentration prediction: comprehensive evaluation and comparison with various machine and deep learning algorithms
To accurately predict tropospheric ozone concentration (O3), it is needed to investigate the
variety of artificial intelligence techniques' performance, such as machine learning, deep …
variety of artificial intelligence techniques' performance, such as machine learning, deep …
Ozone concentration forecasting based on artificial intelligence techniques: a systematic review
The prediction of tropospheric ozone concentrations is vital due to ozone's passive impacts
on atmosphere, people's health, flora and fauna. However, ozone prediction is a complex …
on atmosphere, people's health, flora and fauna. However, ozone prediction is a complex …
[HTML][HTML] Ozone concentration forecasting utilizing leveraging of regression machine learnings: A case study at Klang Valley, Malaysia
Abstract At Klang Valley, ground-level ozone is a significant source of air pollution. Ozone (O
3) concentration is affected by meteorological conditions and air pollutants. Linear …
3) concentration is affected by meteorological conditions and air pollutants. Linear …