Deep neural networks for spatial-temporal cyber-physical systems: A survey

AA Musa, A Hussaini, W Liao, F Liang, W Yu - Future Internet, 2023 - mdpi.com
Cyber-physical systems (CPS) refer to systems that integrate communication, control, and
computational elements into physical processes to facilitate the control of physical systems …

Machine learning for the detection and identification of Internet of Things devices: A survey

Y Liu, J Wang, J Li, S Niu… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) is becoming an indispensable part of everyday life, enabling a
variety of emerging services and applications. However, the presence of rogue IoT devices …

A spatial-temporal approach for multi-airport traffic flow prediction through causality graphs

W Du, S Chen, Z Li, X Cao, Y Lv - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Accurate airport traffic flow estimation is crucial for the secure and orderly operation of the
aviation system. Recent advances in machine learning have achieved promising prediction …

Take an irregular route: Enhance the decoder of time-series forecasting transformer

L Shen, Y Wei, Y Wang, H Qiu - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
With the development of Internet of Things (IoT) systems, precise long-term forecasting
method is requisite for decision makers to evaluate current statuses and formulate future …

FCM-GCN-based upstream and downstream dependence model for air traffic flow networks

Y Zhang, Z Lu, J Wang, L Chen - Knowledge-Based Systems, 2023 - Elsevier
The upstream and downstream dependence of air traffic flow networks (ATFN) is a key step
in identifying the changing characteristics and interaction patterns of air traffic flow. This …

Deep learning architecture for UAV traffic-density prediction

A Alharbi, I Petrunin, D Panagiotakopoulos - Drones, 2023 - mdpi.com
The research community has paid great attention to the prediction of air traffic flows.
Nonetheless, research examining the prediction of air traffic patterns for unmanned aircraft …

Improving Air Mobility for Pre-Disaster Planning with Neural Network Accelerated Genetic Algorithm

K Acharya, A Velasquez, Y Liu, D Liu, L Sun… - arxiv preprint arxiv …, 2024 - arxiv.org
Weather disaster related emergency operations pose a great challenge to air mobility in
both aircraft and airport operations, especially when the impact is gradually approaching …

GraphDAC: A Graph-Analytic Approach to Dynamic Airspace Configuration

K Feng, D Liu, Y Liu, H Liu… - 2023 IEEE 24th …, 2023 - ieeexplore.ieee.org
The current National Airspace System (NAS) is reaching capacity due to increased air traffic,
and is based on outdated pre-tactical planning. This study proposes a more dynamic …

Machine learning-enabled adaptive air traffic recommendation system for disaster evacuation

Y Yang, K Zhang, H Song, D Liu - 2021 IEEE/AIAA 40th Digital …, 2021 - ieeexplore.ieee.org
Extreme weather conditions, such as floods, hurricanes and wildfires, cause large-scale
human population movements and evacuations in the world. Taking flights to evacuate the …

Distillation knowledge-based space-time data prediction on industrial IoT edge devices

Y Zhang, Y **ng, Y Liu, T Zhang - Ad Hoc Networks, 2022 - Elsevier
Abstract In industrial Internet of Things (IIoT), the space–time data prediction algorithm is
considered as one of the key technologies for supporting real-time monitoring and intelligent …