PREDICTIVE MODELING OF FLIGHT DELAYS USING DECISSION TREE
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Abstract
Nowadays, although technology has developed on an unimaginable scale, there are still factors that can disrupt the safe and smooth functioning of many areas of daily life. One such factor are delays. Unquestionably, they are an undesirable and, in some cases, even dangerous element.
A particular case in point may be air traffic, which is one of the most technologically advanced areas. However, air traffic delays, which occur quite frequently, have made it desirable to study this area based on airport capacity modeling and machine learning methods, with the main focus on decision tree algorithms. Based on these decision tree methods, the result of acquiring and processing data and variables has been the creation of specific models that can support air traffic management and, consequently, the levelling of the resulting delays.
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References
Bertsimas D., Lulli G., Odoni A., ‘An Integer Optimization Approach to Large-Scale Air Traffic Flow Management’. Operations Research 59, no. 1 (February 2011): 211–27. https://doi.org/10.1287/opre.1100.0899.
Bilmoria K.D., Sridhar B., Chatterji G.B., Sheth K., Grabbe S., ‘FACET: Future ATM Concepts Evaluation Tool’. Air Traffic Control Quarterly, 2001. https://doi.org/10.2514/atcq.9.1.1.
Bisandu D.B., Homaid M.S., Moulitsas I., Filippone S., ‘A Deep Feedforward Neural Network and Shallow Architectures Effectiveness Comparison: Flight Delays Classification Perspective’, 2021. https://doi.org/10.1145/3505711.3505712.
Chen Y., Jiang Y., Tsai S.-B., Zhu J., ‘An Empirical Study on the Indirect Impact of Flight Delay on China’s Economy’. Sustainability, 2018. https://doi.org/10.3390/su10020357.
Duan L., Zhou J., You W., Xu W. ‘A Novel and Highly Efficient Botnet Detection Algorithm Based on Network Traffic Analysis of Smart Systems’. International Journal of Distributed Sensor Networks, 2022. https://doi.org/10.1177/15501477211049910.
Esmaeilzadeh E., Mokhtarimousavi S., ‘Machine Learning Approach for Flight Departure Delay Prediction and Analysis’. Transportation Research Record Journal of the Transportation Research Board, 2020. https://doi.org/10.1177/0361198120930014.
Graupl T., Mayr M., Rokitansky C.-H., ‘A Method for SWIM-Compliant Human-in-the-Loop Simulation of Airport Air Traffic Management’. International Journal of Aerospace Engineering, 2016. https://doi.org/10.1155/2016/6806198.
Hamami F., Dahlan I.A., ‘Air Quality Classification in Urban Environment Using Machine Learning Approach’. Iop Conference Series Earth and Environmental Science, 2022. https://doi.org/10.1088/1755-1315/986/1/012004.
Izdebski M., Gołda P., Zawisza T., The Use of Simulation Tools to Minimize the Risk of Dangerous Events on the Airport Apron, Lecture Notes in Networks and Systems, 2023, 604 LNNS, pp. 91–107. https://doi.org/10.1007/978-3-031-22359-4_6.
Jia Y., Zhang H., Líu H., Zhong G., Li G., ‘Flight Delay Classification Prediction Based on Stacking Algorithm’. Journal of Advanced Transportation, 2021. https://doi.org/10.1155/2021/4292778.
Jiang X., Xie Y., ‘Study of the Multi-Airport Ground-Holding Strategy Model and Application’, 2016. https://doi.org/10.2991/i3csee-16.2016.4.
Kalliguddi A.M., Leboulluec A.K., ‘Predictive Modeling of Aircraft Flight Delay’. Universal Journal of Management, 2017. https://doi.org/10.13189/ujm.2017.051003.
Khan R.U., Xiaosong Zhang X., Kumar R., Sharif A., Golilarz N.A., Alazab M., ‘An Adaptive Multi-Layer Botnet Detection Technique Using Machine Learning Classifiers’. Applied Sciences, 2019. https://doi.org/10.3390/app9112375.
Li S., Qin J., He M., Paoli R., ‘Fast Evaluation of Aircraft Icing Severity Using Machine Learning Based on XGBoost’. Aerospace, 2020. https://doi.org/10.3390/aerospace7040036.
Moreno R., Luis J., Balakrishnan H., ‘Characterization and Prediction of Air Traffic Delays’. Transportation Research Part C Emerging Technologies, 2014. https://doi.org/10.1016/j.trc.2014.04.007.
Palopo K., Chatterji G.B., Lee H.-T., ‘Interaction of Airspace Partitions and Traffic Flow Management Delay’, 2010. https://doi.org/10.2514/6.2010-9295.
Qu J., Wu S., Zhang J., ‘Flight Delay Propagation Prediction Based on Deep Learning’. Mathematics, 2023. https://doi.org/10.3390/math11030494.
Stefanovič P., Štrimaitis R., Kurasova O., ‘Prediction of Flight Time Deviation for Lithuanian Airports Using Supervised Machine Learning Model’. Computational Intelligence and Neuroscience, 2020. https://doi.org/10.1155/2020/8878681.
Tang B., Kay S., He H., ‘Toward Optimal Feature Selection in Naive Bayes for Text Categorization’. Ieee Transactions on Knowledge and Data Engineering, 2016. https://doi.org/10.1109/tkde.2016.2563436.
Tong D., Qu Y.R., Prasanna V.K., ‘High-Throughput Traffic Classification on Multi-Core Processors’, 2014. https://doi.org/10.1109/hpsr.2014.6900894.
Wang R., ‘A Note on Logistic Regression and Logistic Kernel Machine Models’, 2011. https://doi.org/10.48550/arxiv.1103.0818.
Wong J.-T., Chang Tsai S., ‘A Survival Model for Flight Delay Propagation’. Journal of Air Transport Management, 2012. https://doi.org/10.1016/j.jairtraman.2012.01.016.
Wu Z., Lin W., Ji Y., ‘An Integrated Ensemble Learning Model for Imbalanced Fault Diagnostics and Prognostics’. IEEE Access 6 (2018): 8394–8402. https://doi.org/10.1109/ACCESS.2018.2807121.
Xu G., Zhang X., ‘Statistical Analysis of Resilience in an Air Transport Network’. Frontiers in Physics, 2022. https://doi.org/10.3389/fphy.2022.969311.
Zámková M., Prokop M., Stolín R., ‘Factors Influencing Flight Delays of a European Airline’. Acta Universitatis Agriculturae Et Silviculturae Mendelianae Brunensis, 2017. https://doi.org/10.11118/actaun201765051799.
Zhang J., Bianco G.L., Beck J.Ch., ‘Solving Job-Shop Scheduling Problems with QUBO-Based Specialized Hardware’. Proceedings of the International Conference on Automated Planning and Scheduling 32 (13 June 2022): 404–12. https://doi.org/10.1609/icaps.v32i1.19826.
Zhang K., ‘Spatio-Temporal Data Mining for Aviation Delay Prediction’, 2021. https://doi.org/10.48550/arxiv.2103.11221.
Zhen Y., Yang H., Li F., Lin Y., ‘A Deep Learning Approach for Short-Term Airport Traffic Flow Prediction’. Aerospace, 2021. https://doi.org/10.3390/aerospace9010011.
Ziółkowski J., Małachowski J., Oszczypała M., Szkutnik-Rogoż J., Konwerski J., Simulation model for analysis and evaluation of selected measures of the helicopter’s readiness, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2022, 236(13), pp. 2751–2762. https://doi.org/10.1177/09544100211069180.
Zoutendijk M., Mitici M., ‘Probabilistic Flight Delay Predictions Using Machine Learning and Applications to the Flight-to-Gate Assignment Problem’. Aerospace 8, no. 6 (June 2021): 152. https://doi.org/10.3390/aerospace8060152.