RT Journal Article
T1 Machine learning algorithms to forecast air quality: a survey
A1 Méndez Hurtado, Manuel
A1 García Merayo, María De Las Mercedes
A1 Núñez García, Manuel
AB 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.
PB Springer Nature
YR 2023
FD 2023-02-16
LK https://hdl.handle.net/20.500.14352/104114
UL https://hdl.handle.net/20.500.14352/104114
LA eng
NO 2023 Acuerdos transformativos CRUE
DS Docta Complutense
RD 1 jul 2025