We address air quality (AQ) forecasting as a regression problem employing computational intelligence (CI) methods for the Gdansk Metropolitan Area (GMA) in Poland and the Thessaloniki Metropolitan Area (TMA) in Greece. Linear Regression as well as Artificial Neural Network models are developed, accompanied by Random Forest models, for five locations per study area and for a dataset of limited feature dimensionality. | Revisiting urban air quality forecasting: A regression approach
