A survey on artificial intelligence (ai) and explainable ai in air traffic management: Current trends and development with future research trajectory
Air Traffic Management (ATM) will be more complex in the coming decades due to the
growth and increased complexity of aviation and has to be improved in order to maintain …
growth and increased complexity of aviation and has to be improved in order to maintain …
On the relevance of data science for flight delay research: a systematic review
L Carvalho, A Sternberg, L Maia Goncalves… - Transport …, 2021 - Taylor & Francis
Flight delays are a significant problem for society as they evenly impair airlines, transport
companies, air traffic controllers, facility managers, and passengers. Studying prior flight …
companies, air traffic controllers, facility managers, and passengers. Studying prior flight …
Hierarchical integrated machine learning model for predicting flight departure delays and duration in series
Flight delays may propagate through the entire aviation network and are becoming an
important research topic. This paper proposes a novel hierarchical integrated machine …
important research topic. This paper proposes a novel hierarchical integrated machine …
Flight delay prediction based on deep learning and Levenberg-Marquart algorithm
Flight delay is inevitable and it plays an important role in both profits and loss of the airlines.
An accurate estimation of flight delay is critical for airlines because the results can be …
An accurate estimation of flight delay is critical for airlines because the results can be …
A review on flight delay prediction
A Sternberg, J Soares, D Carvalho… - arXiv preprint arXiv …, 2017 - arxiv.org
Flight delays hurt airlines, airports, and passengers. Their prediction is crucial during the
decision-making process for all players of commercial aviation. Moreover, the development …
decision-making process for all players of commercial aviation. Moreover, the development …
A novel parallel series data-driven model for IATA-coded flight delays prediction and features analysis
Predicting and analysing flight delays is essential for successful air traffic management and
control. We propose a novel parallel-series model and novel adaptive bidirectional extreme …
control. We propose a novel parallel-series model and novel adaptive bidirectional extreme …
[HTML][HTML] An artificial neural network for predicting air traffic demand based on socio-economic parameters
Over the past five years, emerging economies have consistently progressed toward
achieving greater economic independence. The aviation industry has played a significant …
achieving greater economic independence. The aviation industry has played a significant …
Nonlinear model predictive control of a multiscale thin film deposition process using artificial neural networks
G Kimaev, LA Ricardez-Sandoval - Chemical Engineering Science, 2019 - Elsevier
The purpose of this study was to employ Artificial Neural Networks (ANNs) to develop data-
driven models that would enable the shrinking horizon nonlinear model predictive control of …
driven models that would enable the shrinking horizon nonlinear model predictive control of …
A Multilayer Perceptron Neural Network with Selective‐Data Training for Flight Arrival Delay Prediction
Flight delay is the most common preoccupation of aviation stakeholders around the world.
Airlines, which suffer from a monetary and customer loyalty loss, are the most affected …
Airlines, which suffer from a monetary and customer loyalty loss, are the most affected …
Flight delay prediction using deep convolutional neural network based on fusion of meteorological data
J Qu, T Zhao, M Ye, J Li, C Liu - Neural Processing Letters, 2020 - Springer
Nowadays, the civil aviation industry has a high precision demand of flight delay prediction.
To make full use of the characteristics of flight data and meteorological data, two flight delay …
To make full use of the characteristics of flight data and meteorological data, two flight delay …