AIMC Topic: Aviation

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Air transportation carbon dioxide emission forecasting: An improved back propagation neural network.

PloS one
To address the challenges of increasing carbon dioxide (CO2) emissions and climate change caused by the growth of air traffic, accurate prediction of CO2 emissions in civil aviation has become crucial. This study proposes a CO2 emission prediction me...

Quantifying Aviation-Related Contributions to Ambient Ultrafine Particle Number Concentrations Using Interpretable Machine Learning.

Environmental science & technology
Ultrafine particles (UFP, < 100 nm) are abundantly emitted by aircraft, but quantifying their contributions to ambient particle number concentrations (PNC) is challenging due to confounding from local traffic and complex interactions between aircraf...

Recognition of flight cadets brain functional magnetic resonance imaging data based on machine learning analysis.

PloS one
The rapid advancement of the civil aviation industry has attracted significant attention to research on pilots. However, the brain changes experienced by flight cadets following their training remain, to some extent, an unexplored territory compared ...

4D trajectory prediction and conflict detection in terminal areas based on an improved convolutional network.

PloS one
At present, the passenger traffic volume of civil aviation is gradually increasing, and the scale of the airline network is gradually expanding. In order to optimize the air traffic service mode more safely and scientifically, the International Civil...

A networked station system for high-resolution wind nowcasting in air traffic operations: A data-augmented deep learning approach.

PloS one
This study introduces a high-resolution wind nowcasting model designed for aviation applications at Madeira International Airport, a location known for its complex wind patterns. By using data from a network of six meteorological stations and deep le...

Addressing Gearbox Health Monitoring Challenges for Helicopters: A Machine Learning Approach.

Anais da Academia Brasileira de Ciencias
The transmission gearbox of military helicopters, such as the H225M, experiences intense dynamic loads, leading to the detachment of ferromagnetic particles, often due to wear or fatigue. This poses safety risks, as excessive particle detachment dema...

Detection of Pilots' Psychological Workload during Turning Phases Using EEG Characteristics.

Sensors (Basel, Switzerland)
Pilot behavior is crucial for aviation safety. This study aims to investigate the EEG characteristics of pilots, refine training assessment methodologies, and bolster flight safety measures. The collected EEG signals underwent initial preprocessing. ...

Enhancing Aviation Safety through AI-Driven Mental Health Management for Pilots and Air Traffic Controllers.

Cyberpsychology, behavior and social networking
This article provides an overview of the mental health challenges faced by pilots and air traffic controllers (ATCs), whose stressful professional lives may negatively impact global flight safety and security. The adverse effects of mental health dis...

Detecting and Predicting Pilot Mental Workload Using Heart Rate Variability: A Systematic Review.

Sensors (Basel, Switzerland)
Measuring pilot mental workload (MWL) is crucial for enhancing aviation safety. However, MWL is a multi-dimensional construct that could be affected by multiple factors. Particularly, in the context of a more automated cockpit setting, the traditiona...

SegX-Net: A novel image segmentation approach for contrail detection using deep learning.

PloS one
Contrails are line-shaped clouds formed in the exhaust of aircraft engines that significantly contribute to global warming. This paper confidently proposes integrating advanced image segmentation techniques to identify and monitor aircraft contrails ...