Analysis of the Quality of the Associations of Pollutants and Meteorological Variables by Seasonality

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Published : 2023-10-15
DOI : https://doi.org/10.37815/rte.v35n2.1052
Keywords :
Decision tree, discretization, artificial intelligence, data mining, association rules
Jorge Luis Zambrano-Martinez
https://orcid.org/0000-0002-5339-7860
Marcos Orellana
https://orcid.org/0000-0002-3671-9362
Agustin Ferrari
https://orcid.org/0009-0009-5696-8954
Alex Coro
https://orcid.org/0009-0009-6020-3751
Sebastian Heras
https://orcid.org/0009-0001-9148-0139
Abstract

To achieve a more accurate assessment of air quality, it is necessary to know the relationship between meteorological variables and the different air pollutants; this will also be aimed at avoiding the risks present both in the ecosystem and in human health in the future. The problem begins with finding an association between air pollutants and meteorological variables in the models and categorization methods that can be used. Due to this reason, the objective of this article is to analyze the quality of the associations between pollutants and meteorological variables by seasonality using decision trees to find knowledge that allows locating patterns that will be important for environmental analysis. Therefore, it was possible to achieve a periodic control of the quality of the associations of pollutants and meteorological variables, whose validation of the confidence level of the association rules is greater than 70% in the months studied.

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Zambrano-Martinez, J. L., Orellana, M., Ferrari Ferrari, D. A., Coro, A., & Heras, S. (2023). Analysis of the Quality of the Associations of Pollutants and Meteorological Variables by Seasonality. Revista Tecnológica - ESPOL, 35(2), 50-60. https://doi.org/10.37815/rte.v35n2.1052
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Author Biography

Jorge Luis Zambrano-Martinez

Jorge Luis Zambrano-Martinez is a Ph.D. in Computer Science received in Department of Networking Research Group (GRC) at the Universitat Politècnica de València (UPV) from Spain in 2019, included an awarded international doctoral and an awarded Cum Laude. He graduated in Master's Degree in Information and Communication Technology Security at Universitat Oberta de Catalunya in 2018. He graduated in Master’s Degree in Computer Engineering at Universitat Politècnica de València (UPV) in 2015. He graduated in Systems Engineering at Polytechnic University Salesian (Ecuador) in 2011. His research interests include Vehicular Networks, Smart Cities & IoT, Network Security, ITS, and Computer Vision.

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