Influencia de las condiciones meteorológicas en los retrasos de vuelos: un estudio predictivo del Aeropuerto Internacional O'Hare
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2024
Defense date
06/2024
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Abstract
Este estudio aborda la problemática de los retrasos de vuelos en el Aeropuerto Internacional O'Hare de Chicago, utilizando datos recopilados del Departamento de Transporte de los Estados Unidos (DOT) y del Centro Nacional de Información Ambiental (NCEI). Se desarrollaron modelos de predicción de retrasos de vuelos basados en variables meteorológicas, utilizando técnicas de regresión logística binomial, árboles de clasificación, bosques aleatorios y XGBoost. Los resultados revelan la influencia significativa de las condiciones meteorológicas en los retrasos de vuelos y demuestran la eficacia de los modelos propuestos para predecir estos retrasos con precisión.
Abstract This study addresses the issue of flight delays at Chicago O'Hare International Airport, using data collected from the United States Department of Transportation (DOT) and the National Centers for Environmental Information (NCEI). Predictive models for flight delays were developed based on weather variables, utilizing binomial logistic regression, classification trees, random forests, and XGBoost techniques. The results reveal the significant influence of weather conditions on flight delays and demonstrate the effectiveness of the proposed models in accurately predicting these delays.
Abstract This study addresses the issue of flight delays at Chicago O'Hare International Airport, using data collected from the United States Department of Transportation (DOT) and the National Centers for Environmental Information (NCEI). Predictive models for flight delays were developed based on weather variables, utilizing binomial logistic regression, classification trees, random forests, and XGBoost techniques. The results reveal the significant influence of weather conditions on flight delays and demonstrate the effectiveness of the proposed models in accurately predicting these delays.