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Management and Operations

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Embry-Riddle Aeronautical University

International Journal of Aviation, Aeronautics, and Aerospace

Machine Learning

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Articles 1 - 2 of 2

Full-Text Articles in Engineering

Classifıcation Of Survivor/Non-Survivor Passengers In Fatal Aviation Accidents: A Machine Learning Approach, Tüzün Tolga İnan Dr. Jan 2022

Classifıcation Of Survivor/Non-Survivor Passengers In Fatal Aviation Accidents: A Machine Learning Approach, Tüzün Tolga İnan Dr.

International Journal of Aviation, Aeronautics, and Aerospace

The safety concept primarily examines the most fatal (resulting in dead passengers) accidents of aviation history in this study. The primary causes of most fatal accidents are; human, technical, and sabotage/terrorism factors. Although the aviation industry started with the first engine flight in 1903, the safety concept has been examined since the 1950s. The safety concept firstly examined the technical factors, and in the late 1970s, human factors started to analyze. Despite these primary causes, there have different factors that affect accidents. So, the study aims to determine the affecting factors of the most fatal accidents to classify the survivor/non-survivor …


Predictability Improvement Of Scheduled Flights Departure Time Variation Using Supervised Machine Learning, Deepudev Sahadevan, Palanisamy Ponnusamy Dr, Manjunath K. Nelli Mr, Varun P. Gopi Dr Jan 2021

Predictability Improvement Of Scheduled Flights Departure Time Variation Using Supervised Machine Learning, Deepudev Sahadevan, Palanisamy Ponnusamy Dr, Manjunath K. Nelli Mr, Varun P. Gopi Dr

International Journal of Aviation, Aeronautics, and Aerospace

The departure time uncertainty exacerbates the inaccuracy of arrival time estimation and demand for arrival slots, particularly for movements to capacity constrained airports. The Estimated Take-Off Time (ETOT) or Estimated Departure Time(ETD) for each individual flight is currently derived from Air Traffic Flow Management System (ATFMS), which are solely determined based on individual flight plan Estimated Off Block Time(EOBT) or subsequent delays updated by Airline. Even if normal weather conditions prevail, aircraft departure times will differ from ETOTs determined by the ATFMS due to a number of factors such as congestion, early/delayed inbound flight (linked flights), reactionary delays and air …