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Airports

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Prediction of Flight Time Deviation for Lithuanian Airports Using Supervised Machine Learning Model.

Computational intelligence and neuroscience
In the paper, the flight time deviation of Lithuania airports has been analyzed. The supervised machine learning model has been implemented to predict the interval of time delay deviation of new flights. The analysis has been made using seven algorit...

A rainwater control optimization design approach for airports based on a self-organizing feature map neural network model.

PloS one
To address the problems of high overflow rate of pipe network inspection well and low drainage efficiency, a rainwater control optimization design approach based on a self-organizing feature map neural network model (SOFM) was proposed in this paper....

Lightweight convolutional neural network for aircraft small target real-time detection in Airport videos in complex scenes.

Scientific reports
Airport aircraft identification has essential application value in conflict early warning, anti-runway foreign body intrusion, remote command, etc. The scene video images have problems such as small aircraft targets and mutual occlusion due to the ex...

A Deep Learning Framework for Real-Time Bird Detection and Its Implications for Reducing Bird Strike Incidents.

Sensors (Basel, Switzerland)
Bird strikes are a substantial aviation safety issue that can result in serious harm to aircraft components and even passenger deaths. In response to this increased tendency, the implementation of new and more efficient detection and prevention techn...

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...