Analysis of the Behavior of the Ozone Time Series in México City Using Machine Learning Trend 2010 - 2024

This new study includes an analysis and forecast of the time series of daily ozone maxima for 2024 and daily concentrations, plus a trend from 2010 to 2024 for the case of daily ozone maxima in Mexico City, Machine Learning and Deep Learning algorithms are used to study the behavior, as well as the classic ARIMA method for evaluation of the forecast model.RMSE, MSE, MAE and MAPE were used.

Authors

Publication Details

Journal
International journal of latest research in engineering and technology.
Published
2025-04-11
DOI
https://doi.org/10.56581/ijlret.11.04.09-25
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
0.00
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article

Analysis of the Behavior of the Ozone Time Series in México City Using Machine Learning Trend 2010 - 2024

Zenteno Jiménez José Roberto
International journal of latest research in engineering and technology.
Air Quality Monitoring and Forecasting
article

Analysis of the Behavior of the Ozone Time Series in México City Using Machine Learning Trend 2010 - 2024

Zenteno Jiménez José Roberto
article en

Abstract

This new study includes an analysis and forecast of the time series of daily ozone maxima for 2024 and daily concentrations, plus a trend from 2010 to 2024 for the case of daily ozone maxima in Mexico City, Machine Learning and Deep Learning algorithms are used to study the behavior, as well as the classic ARIMA method for evaluation of the forecast model.RMSE, MSE, MAE and MAPE were used.

International journal of latest research in engineering and technology.Vol. 11(4)
Climate action
Openalex Percentile: Top 91%
Air Quality Monitoring and Forecasting
DOIOpen Access PDFOpenAlex
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Analysis of the Behavior of the Ozone Time Series in México City Using Machine Learning Trend 2010 - 2024 — Zenteno Jiménez José Roberto · International journal of latest research in engineering and technology. (2025) | TGRS Research Map | TGRS