Aircraft trajectory clustering in terminal airspace based on deep autoencoder and gaussian mixture model
The aircraft trajectory clustering analysis in the terminal airspace is conducive to determining
the representative route structure of the arrival and departure trajectory and extracting their …
the representative route structure of the arrival and departure trajectory and extracting their …
Classification and analysis of go-arounds in commercial aviation using ADS-B data
Go-arounds are a necessary aspect of commercial aviation and are conducted after a
landing attempt has been aborted. It is necessary to conduct go-arounds in the safest …
landing attempt has been aborted. It is necessary to conduct go-arounds in the safest …
[HTML][HTML] Transport patterns of global aviation NO and their short-term O radiative forcing – a machine learning approach
J Maruhashi, V Grewe, C Frömming… - Atmospheric …, 2022 - acp.copernicus.org
Aviation produces a net climate warming contribution that comprises multiple forcing terms
of mixed sign. Aircraft NO x emissions are associated with both warming and cooling terms …
of mixed sign. Aircraft NO x emissions are associated with both warming and cooling terms …
A clustering-based quantitative analysis of the interdependent relationship between spatial and energy anomalies in ADS-B trajectory data
As air traffic demand grows, robust, data-driven methods are required to ensure that aviation
systems become safer and more efficient. The terminal airspace is identified as the most …
systems become safer and more efficient. The terminal airspace is identified as the most …
[HTML][HTML] Flight data clustering for offline evaluation of real-time trajectory optimization framework
Abstract Real-time Trajectory Optimization (RTOP) is a machine learning-based flight path
optimization framework that automatically performs in-flight re-planning continuously with …
optimization framework that automatically performs in-flight re-planning continuously with …
Multiclass multiple-instance learning for predicting precursors to aviation safety events
In recent years, there has been a rapid growth in applying machine learning techniques that
leverage aviation data collected from commercial airline operations to improve safety …
leverage aviation data collected from commercial airline operations to improve safety …
Hierarchical Method for Mining a Prevailing Flight Pattern in Airport Terminal Airspace
Due to the variety of flight patterns in airport terminal airspace, as well as the high global
similarity of different flight patterns entering and leaving from the same runway or corridor, it …
similarity of different flight patterns entering and leaving from the same runway or corridor, it …
Modeling and characterization of traffic flow patterns and identification of airspace density for UTM application
AA Alharbi, I Petrunin, D Panagiotakopoulos - IEEE Access, 2022 - ieeexplore.ieee.org
Current airspace has limited resources, and the widespread use of unmanned aerial
vehicles (UAVs) increases airspace density, which is already crowded with manned aircraft …
vehicles (UAVs) increases airspace density, which is already crowded with manned aircraft …
Trajectory clustering for air traffic categorisation
Availability of different types of data and advances in data-driven techniques open the path
to more detailed analyses of various phenomena. Here, we examine the insights that can be …
to more detailed analyses of various phenomena. Here, we examine the insights that can be …
Application of trajectory clustering for aircraft conflict detection
This paper presents the application of machine learning and open-source data to improve
the prediction capability of conflict between aircraft in terminal airspace. An analytical …
the prediction capability of conflict between aircraft in terminal airspace. An analytical …