Improving airport arrival flow prediction considering heterogeneous and dynamic network dependencies

Z Yan, H Yang, D Guo, Y Lin - Information Fusion, 2023 - Elsevier
Predicting airport arrival flow serves as a crucial technique in air traffic flow management.
Given the unique operational characteristics of air traffic systems, airport arrival flow …

A multi-view attention-based spatial–temporal network for airport arrival flow prediction

Z Yan, H Yang, Y Wu, Y Lin - Transportation Research Part E: Logistics and …, 2023 - Elsevier
Accurate airport arrival flow prediction is a precondition for intelligent air traffic flow
management. However, most existing studies focus on the dynamic traffic flow in a single …

[HTML][HTML] A deep learning approach for short-term airport traffic flow prediction

Z Yan, H Yang, F Li, Y Lin - Aerospace, 2021 - mdpi.com
Airport traffic flow prediction is a fundamental research topic in the field of air traffic flow
management. Most existing works focus on the single airport traffic flow prediction with …

[HTML][HTML] Pedestrian flow prediction in open public places using graph convolutional network

M Liu, L Li, Q Li, Y Bai, C Hu - ISPRS International Journal of Geo …, 2021 - mdpi.com
Open public places, such as pedestrian streets, parks, and squares, are vulnerable when
the pedestrians thronged into the sidewalks. The crowd count changes dynamically over …

Fifteenth USA/Europe Air Traffic Management Research and Development Seminar (ATM2023) STL combining LSTM for long-term predicting airport traffic flow

Z Wang, Y Wang, Y Zhao, M Hansen… - US-Europe ATM …, 2023 - enac.hal.science
Airport traffic flow exhibits significant periodicity on a daily scale, few studies have given
attention to periodicity when predicting airport traffic flow. In this article, we propose a novel …

A short-term traffic forecasting model based on wavelet neural network with novel teaching learning based optimization

Q Zhang, Z Ye, Y Ding, F Su - 2020 39th Chinese Control …, 2020 - ieeexplore.ieee.org
Short-term traffic flow prediction is of vital significance to traffic monitoring and induction. It is
a nonlinear problem with considerable uncertainty. In this paper, a novel teaching-learning …