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A Deep Learning Method for Predicting Terminal Air Traffic Congestion Levels Based on Multimode Spatiotemporal Propagation Networks

Year: 2025

Type: article

Source: IEEE Transactions on Intelligent Transportation Systems

DOI: 10.1109/tits.2025.3610514

Authors: Shanmei Li, Duanyang Wang, Siying Xu, Yuxin Wang, Mo Zhao

Institutions: Civil Aviation University of China, Civil Aviation Administration of China

Language: English

Topic: Air Traffic Management and Optimization

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: closed

Funders: National Natural Science Foundation of China, Adelaide Research and Innovation, University of Adelaide, Fundamental Research Funds for the Central Universities

Awards: G2773883958, 数据驱动的区域航空网络拥挤状态演化机理研究, G7549648640, G830063094

OpenAlex ID: W4414431930

FWCI: 1.199

Cites: 32

Cited by: 3

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