Distribution Prediction of Strategic Flight Delays via Machine Learning Methods

Article Economics

Timescales of delay propagation in airport networks

Yanjun Wang et al.

Summary: This article introduces an algorithm to estimate time lags between airport delays and analyzes the US airport delays in 2017. The research results have potential implications for delay prediction models and airline schedule design.

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW (2022)

添加到收藏夹

Article Transportation

Characterization of delay propagation in the air traffic network

Qiang Li et al.

Summary: A delay propagation network was constructed based on Bayesian Network approach to investigate delay propagation among the 100 busiest airports in the United States. Results showed that the cumulative degree distribution of the network follows an exponential function and flight delays typically require at most one transhipment.

JOURNAL OF AIR TRANSPORT MANAGEMENT (2021)

添加到收藏夹

Article Engineering, Multidisciplinary

A Spatial-Temporal Network Perspective for the Propagation Dynamics of Air Traffic Delays

Qing Cai et al.

Summary: This study focuses on the dynamics of delay propagation in air traffic, presenting a complex network perspective to model the aviation system. By using airports as nodes and establishing dynamic edges, experiments show that the delay propagation magnitude and speed in the US are significantly higher than those in the Southeastern Asia region.

ENGINEERING (2021)

添加到收藏夹

Article Transportation Science & Technology

Hierarchical integrated machine learning model for predicting flight departure delays and duration in series

Waqar Ahmed Khan et al.

Summary: This study proposes a novel hierarchical integrated machine learning model for predicting flight departure delays and duration, which is validated using practical data and shows good accuracy in classifying delay status and predicting delay duration.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2021)

添加到收藏夹

Article Transportation Science & Technology

Flight time prediction for fuel loading decisions with a deep learning approach

Xinting Zhu et al.

Summary: A novel spatial weighted recurrent neural network model was developed to provide better flight time predictions by capturing air traffic information, which helps optimize fuel loading and reduce fuel consumption.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2021)

添加到收藏夹

Article Engineering, Aerospace

Probabilistic Flight Delay Predictions Using Machine Learning and Applications to the Flight-to-Gate Assignment Problem

Micha Zoutendijk et al.

Summary: Probabilistic forecasting algorithms were successfully applied to predict flight delays at a European airport, demonstrating the utility of probabilistic delay predictions in optimizing airport operations. The proposed probabilistic flight-to-gate assignment model performed well, significantly reducing the number of conflicted aircraft.

AEROSPACE (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence