한국항공운항학회지 (Journal of the Korean Society for Aviation and Aeronautics)

  • 제29권2호
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  • Pages.84-93
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  • 2021
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  • 1225-9705(pISSN)
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  • 2466-1791(eISSN)
한국항공운항학회 (The Korean Society for Aviation and Aeronautics)
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항공사 기단의 상태변화 시각화에 관한 연구

A Study on the Visualization of an Airline's Fleet State Variation

  • 이용화 (한국항공대학교 항공교통물류학과) ;
  • 이주환 (한국항공대학교 항공교통물류학과) ;
  • 이금진 (한국항공대학교 항공교통물류학부)
  • 투고 : 2021.05.03
  • 심사 : 2021.05.25
  • 발행 : 2021.06.30
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초록

Airline schedule is the most basic data for flight operations and has significant importance to an airline's management. It is crucial to know the airline's current schedule status in order to effectively manage the company and to be prepared for abnormal situations. In this study, machine learning techniques were applied to actual schedule data to examine the possibility of whether the airline's fleet state could be artificially learned without prior information. Given that the schedule is in categorical form, One Hot Encoding was applied and t-SNE was used to reduce the dimension of the data and visualize them to gain insights into the airline's overall fleet status. Interesting results were discovered from the experiments where the initial findings are expected to contribute to the fields of airline schedule health monitoring, anomaly detection, and disruption management.

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과제정보

본 연구는 국토교통과학기술진흥원의 "데이터기반 항공교통관리 기술개발" 과제의 일환으로 수행되었으며 지원에 감사드립니다.

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