2026-06-01T18:34:25Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/1041142024-05-16T23:45:37Zcom_20.500.14352_14col_20.500.14352_15

Machine learning algorithms to forecast air quality: a survey Méndez Hurtado, Manuel García Merayo, María De Las Mercedes Núñez García, Manuel Machine learning Deep learning Regression algorithms Air quality Informática (Informática) 33 Ciencias Tecnológicas 2023 Acuerdos transformativos CRUE Air pollution is a risk factor for many diseases that can lead to death. Therefore, it is important to develop forecasting mechanisms that can be used by the authorities, so that they can anticipate measures when high concentrations of certain pollutants are expected in the near future. Machine Learning models, in particular, Deep Learning models, have been widely used to forecast air quality. In this paper we present a comprehensive review of the main contributions in the field during the period 2011–2021. We have searched the main scientific publications databases and, after a careful selection, we have considered a total of 155 papers. The papers are classified in terms of geographical distribution, predicted values, predictor variables, evaluation metrics and Machine Learning model. Depto. de Sistemas Informáticos y Computación Fac. de Informática TRUE pub APC financiada por la UCM 2024-05-16T15:22:11Z 2024-05-16T15:22:11Z 2023-02-16 journal article VoR https://hdl.handle.net/20.500.14352/104114 XXXX-XXXX 10.1007/s10462-023-10424-4 eng Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ open access application/pdf Springer Nature