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An Analysis of Brazilian Flight Delays Based on Frequent Patterns

Authors: Alice Sternberg, Diego Carvalho, Leonardo Murta, Jorge Soares and Eduardo Ogasawara

Federal Center for Technological Education of Rio de Janeiro (CEFET/RJ)

Abstract: In this paper, we applied data indexing techniques combined with association rules to unveil hidden patterns of flight delays. Considering Brazilian flight data and guided by six research questions related to causes, moments, differences, and relationships between airports and airlines, we evaluated and quantified all attributes that may lead to delays, showing not only the main patterns, but also their chances of occurrence in the entire network, in each airport and airline. We observed that Brazilian flight system has difficulties to recover from previous delays and when operating under adverse meteorological conditions, delays occurrences may increase up to 216%.

Acknowledgments: The authors thank CNPq and FAPERJ for partially sponsoring this research.

 

Eduardo Ogasawara

Eduardo Ogasawara has been a professor at the Department of Computer Science at the Federal Center for Technological Education of Rio de Janeiro (CEFET/RJ) since 2010. He holds a D.Sc. in Systems and Computer Engineering from COPPE/UFRJ. Between 2000 and 2007, he worked in the Information Technology (IT) sector, gaining extensive experience in workflows and project management. With a strong background in Data Science, he is currently focused on Data Mining and Time Series Analysis. He is a member of IEEE, ACM, and SBC. Throughout his career, he has authored numerous published articles and led projects funded by agencies such as CNPq and FAPERJ. Currently, he heads the Data Analytics Lab (DAL) at CEFET/RJ, where he continues to advance research in Data Science.