Text-Enriched Air Traffic Flow Modeling and Prediction Using Transformers-Reference-Cited by-同舟云学术

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Text-Enriched Air Traffic Flow Modeling and Prediction Using Transformers

Published:2024-07 Issue:7 Volume:25 Page:7963-7976
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Ma Chunyao¹^ORCID,Alam Sameer¹^ORCID,Cai Qing²^ORCID,Delahaye Daniel³

Affiliation:

1. Air Traffic Management Research Institute (ATMRI), School of Mechanical and Aerospace Engineering, Nanyang Technological University, Jurong West, Singapore

2. School of Electronic Engineering, Xidian University, Xi’an, China

3. OPTIM Laboratory, École Nationale de l’Aviation Civile, Toulouse, France

Funder

National Research Foundation, Singapore

Civil Aviation Authority of Singapore

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6979/10582787/10493078.pdf?arnumber=10493078

Reference42 articles.

1. Data-Driven Optimization for Air Traffic Flow Management with Trajectory Preferences

2. Business models for flight-centric air traffic control

3. Dynamic air traffic flow coordination for flow-centric airspace management;Ma

4. From aircraft tracking data to network delay model: A data-driven approach considering en-route congestion

5. DART: A machine-learning approach to trajectory prediction and demand-capacity balancing;Fernandez

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