• Journal of the Korean Society for Aviation and Aeronautics
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• v.32 no.2
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• pp.142-150
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• 2024

Improving transportation accessibility on islands is closely related to regional development. Currently, the government is constructing Ulleung Airport as part of the 6th Airport Mid- to Long-term Development Plan. Similar to the case of Jeju Airport in 2016, severe congestion occurs at passenger terminals upon flight resumption after cancellations at airports on islands. Therefore, considering the cancellation rate at island airports is important. This study investigates the conditions leading to increased cancellation rates at Ulleung Airport, with the research results predicting frequent cancellations during the winter season. The research methodology involved examining airport construction plans, aircraft performance, airport de-icing capabilities, and also included consideration of weather conditions. Ulleung Island is a representative snowfall area, and sufficient snow removal capacity must be secured. However, the current plan's snow removal capacity is insufficient, leading to anticipated high cancellation rates. Therefore, measures to mitigate passenger inconvenience caused by increased cancellations and methods to reduce the cancellation rate are explored. With Ulleung Airport scheduled to open in 2027, there is ample time to implement supplementary measures to reduce the cancellation rate and minimize passenger inconvenience.

• The Journal of Information Systems
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• v.31 no.3
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• pp.177-195
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• 2022

Purpose This paper aims to prepare a full operational readiness by establishing an optimal flight plan considering the weather conditions in order to effectively perform the mission and operation of military aircraft. This paper suggests a flight prediction model and rules by analyzing the correlation between flight implementation and cancellation according to weather conditions by using big data collected from historical flight information of military aircraft supplied by Korean manufacturers and meteorological information from the Korea Meteorological Administration. In addition, by deriving flight rules according to weather information, it was possible to discover an efficient flight schedule establishment method in consideration of weather information. Design/methodology/approach This study is an analytic study using data mining techniques based on flight historical data of 44,558 flights of military aircraft accumulated by the Republic of Korea Air Force for a total of 36 months from January 2013 to December 2015 and meteorological information provided by the Korea Meteorological Administration. Four steps were taken to develop optimal flight prediction models and to derive rules for flight implementation and cancellation. First, a total of 10 independent variables and one dependent variable were used to develop the optimal model for flight implementation according to weather condition. Second, optimal flight prediction models were derived using algorithms such as logistics regression, Adaboost, KNN, Random forest and LightGBM, which are data mining techniques. Third, we collected the opinions of military aircraft pilots who have more than 25 years experience and evaluated importance level about independent variables using Python heatmap to develop flight implementation and cancellation rules according to weather conditions. Finally, the decision tree model was constructed, and the flight rules were derived to see how the weather conditions at each airport affect the implementation and cancellation of the flight. Findings Based on historical flight information of military aircraft and weather information of flight zone. We developed flight prediction model using data mining techniques. As a result of optimal flight prediction model development for each airbase, it was confirmed that the LightGBM algorithm had the best prediction rate in terms of recall rate. Each flight rules were checked according to the weather condition, and it was confirmed that precipitation, humidity, and the total cloud had a significant effect on flight cancellation. Whereas, the effect of visibility was found to be relatively insignificant. When a flight schedule was established, the rules will provide some insight to decide flight training more systematically and effectively.