A data analytics approach for anticipating congested days at the São Paulo International Airport

Predictive classification and understanding of weather impact on airport performance through machine learning

“…The analysis of local airport situations allows anticipating congested times and mitigating the negative impact of delays to operations to airline and airport operations (Arnaldo Scarpel and Pelicioni, 2018;Henriques and Feiteira, 2018). Here, historical data provide a profound basis to improve weather forecast using data analytics and machine learning approaches (Rozas Larraondo et al, 2018;Reitmann and Schultz, 2018;Herrema et al, 2019) for fog forecast (Ming et al, 2019), forecast of poor-visibility episodes near complex terrain (Fernández-González et al, 2019) or develop a robust model for learning and recognizing weather pattern (Salman et al, 2018).…”