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머신러닝(Machine Learning) 기법을 활용한 제주국제공항의 운항 지연과의 상관관계 분석 및 지연 여부 예측모형 개발 - 기상을 중심으로 -

Development of a Prediction Model and Correlation Analysis of Weather-induced Flight Delay at Jeju International Airport Using Machine Learning Techniques

  • 이충섭 (한국항공대학교 항공교통물류학과) ;
  • ;
  • 여혜민 (한국항공대학교 항공교통물류학과) ;
  • 김동신 (한국항공대학교 항공교통물류학과) ;
  • 백호종 (한국항공대학교 항공교통물류학과)
  • 투고 : 2021.11.05
  • 심사 : 2021.12.21
  • 발행 : 2021.12.31

초록

Due to the recent rapid increase in passenger and cargo air transport demand, the capacity of Jeju International Airport has been approaching its limit. Even though in COVID-19 crisis which has started from Nov 2019, Jeju International Airport still suffers from strong demand in terms of air passenger and cargo transportation. However, it is an undeniable fact that the delay has also increased in Jeju International Airport. In this study, we analyze the correlation between weather and delayed departure operation based on both datum collected from the historical airline operation information and aviation weather statistics of Jeju International Airport. Adopting machine learning techniques, we then analyze weather condition Jeju International Airport and construct a delay prediction model. The model presented in this study is expected to play a useful role to predict aircraft departure delay and contribute to enhance aircraft operation efficiency and punctuality in the Jeju International Airport.

키워드

과제정보

본 연구는 국토교통과학기술진흥원 "데이터기반 항공교통관리기술개발(과제번호: 21DATM- C162722-01)"의 연구지원으로 수행되었습니다.

참고문헌

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