Aviation research, sourced & cited.

Forecasting Aviation Carbon Emissions with Tree-Based Machine Learning: A Case Study of Turkish Airlines Operational Data

The global aviation industry plays a critical role in economic development and international connectivity. However, it also contributes significantly to environmental challenges, particularly through fuel consumption and…

Generalizing Classification of Pilot Workload: Transfer Learning versus a JEPA-Inspired Transformer Architecture

Within the context of learning, there poses difficulty when objectively measuring human performance. In this work, we investigate the evaluation of human performance via its relation to the individual's mental capacity b…

Using Natural Language Processing to Identify Mental Health Indicators in Aviation Voluntary Safety Reports

Voluntary Safety Reporting Programs (VSRPs) are a critical tool in the aviation industry for monitoring safety issues observed by the frontline workforce.

Real-Time Detection of Sea Turtles Using UAV and Neural Networks on Edge Devices

Sea turtle populations continue to diminish around the globe for various reasons. Therefore, the need for innovative solutions to monitor sea turtles has been increasing.

Identifying Aircraft Damage Mitigating Factors with Explainable Artificial Intelligence (XAI): An Evidence-Based Approach to Rule-Making for Pilot Training Schools

Recent pilot shortages have brought pilot training into focus as the industry attempts to rectify a compounding problem. The FAA has implemented some recent rule-making regarding pilot training that has left the General …

The Intellectual Structure and the Future of Counter-Uncrewed Aerial Systems (UAS) Research: A Bibliometric and A Scoping Review

With advancements in remote sensing technology and affordable design, uncrewed aerial systems (UAS), commonly known as drones, have become prevalent in civil and military applications, such as agriculture, public safety,…

Predicting Expect Departure Clearance Times Based on Surface Weather Observations for a Major Hub Airport: A Machine Learning Approach

Commercial air travel in the United States has grown significantly in the past decade. While the reasons for air traffic delays can vary, weather is the largest cause of flight cancellations and delays in the United Stat…

Utilizing Deep Learning to Predict Unstabilized Approaches for General Aviation Aircraft

Unstabilized approaches pose a major hazard for general aviation aircraft. In the period from 2009 to 2019, 3,257 general aviation accidents occurred during the landing phase of flight in which loss of control was analyz…

Classifıcation of Survivor/Non-Survivor Passengers in Fatal Aviation Accidents: A Machine Learning Approach

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 fa…

Air passenger demand forecast through the use of Artificial Neural Network algorithms

Airport planning depends to a large extent on the levels of activity that are anticipated. In order to plan facilities and infrastructures of an airport system and to be able to satisfy future needs, it is essential to p…

Air passenger demand forecast through the use of Artificial Neural Network algorithms

Airport planning depends to a large extent on the levels of activity that are anticipated. To plan the facilities and infrastructures of an airport system and to be able to satisfy future needs, it is essential to predic…

Implementing Artificial Intelligence and Machine Learning into Advanced Qualification Programs

Since its start, the Advanced Qualification Program (AQP) has encouraged new and innovative strategies for training airline crewmembers.

Predictability improvement of Scheduled Flights Departure Time Variation using Supervised Machine Learning

The departure time uncertainty exacerbates the inaccuracy of arrival time estimation and demand for arrival slots, particularly for movements to capacity constrained airports.

Automatic Gaze Classification for Aviators: Using Multi-task Convolutional Networks as a Proxy for Flight Instructor Observation

In this work, we investigate how flight instructors observe aviator scan patterns and assign quality to an aviator's gaze. We first establish the reliability of instructors to assign similar quality to an aviator's scan …

Predicting the U.S. Airline Operating Profitability using Machine Learning Algorithms

With the increasing competition and cost pressures, the U.S. airline industry has explored methods to reduce operating costs and diversify revenue sources for improving financial performance.