PREDICTION OF FLIGHT DELAYS USING MACHINE LEARNING ALGORITHMS
DOI:
https://doi.org/10.24867/28BE27ZerajicKeywords:
flight delay prediction, exploratory data analysis, system model, KNN, SVM, XGBoost, Random ForestAbstract
This paper tackles the problem of flight delays. In more developed countries, where flight delays can lead to significant financial loss, institutions are founded to monitor and analyze this problem. This paper analyses the factors that influence flight delays by training machine learning models on data on flights, planes, airports, and weather conditions at the time of flight. Flight delays are divided into three classes: negligible delays (up to 15 minutes), small delays (between 15 and 60 minutes), and long delays (over 60 minutes).
References
[1] Mustafa Kurt (2019), MEF university, Flight delay prediction https://openaccess.mef.edu.tr/xmlui/bitstream/handle/20.500.11779/1217/MustafaKurt.pdf
[2] Enwew Chibuike Kenneth (2019), National College of Ireland, A Machine Learning approach predicting flight arrival delay reduction for Delta Airlines https://norma.ncirl.ie/4305/1/chibuikekennethenwere.pdf
[3] Deepak Kulkarni, Yao Wang and Banavar Sridhar (2013), Ames Research Center, Data mining for understanding and improving decision-making affecting ground delay programs
https://permanent.access.gpo.gov/gpo52894/20140008891.pdf
[4] Keggle, 2015 Flight Delays and Cancellations, https://www.kaggle.com/datasets/usdot/flight-delays
[5] FlightAware, Flight Tracker/Flight Status
https://flightaware.com
[6] Open-Meteo, Free Open-Source Weather API
https://open-meteo.com
[2] Enwew Chibuike Kenneth (2019), National College of Ireland, A Machine Learning approach predicting flight arrival delay reduction for Delta Airlines https://norma.ncirl.ie/4305/1/chibuikekennethenwere.pdf
[3] Deepak Kulkarni, Yao Wang and Banavar Sridhar (2013), Ames Research Center, Data mining for understanding and improving decision-making affecting ground delay programs
https://permanent.access.gpo.gov/gpo52894/20140008891.pdf
[4] Keggle, 2015 Flight Delays and Cancellations, https://www.kaggle.com/datasets/usdot/flight-delays
[5] FlightAware, Flight Tracker/Flight Status
https://flightaware.com
[6] Open-Meteo, Free Open-Source Weather API
https://open-meteo.com
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Published
2024-09-05
Issue
Section
Electrotechnical and Computer Engineering
