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

https://doi.org/10.1109/ITSC58415.2024.10920105

Acharya, Kamal; Velasquez, Alvaro; Liu, Yongxin; Liu, Dahai; Sun, Liang; Song, Houbing Herbert (September 2024, IEEE)

Free, publicly-accessible full text available September 24, 2025
A Graph-Analytic Approach to Dynamic Airspace Configuration

https://doi.org/10.1109/IRI58017.2023.00048

Feng, Ke; Liu, Dahai; Yongxin Liu; Liu, Hong; Song, Houbin (August 2023, IEEE Computer Society Conference Publishing Services (CPS) http://www.computer.org/cps)
Cristina Ceballos (Ed.)
The current National Airspace System (NAS) is reaching capacity due to increased air traffic, and is based on outdated pre-tactical planning.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 airspace configuration (DAC) approach that could increase throughput and accommodate fluctuating traffic, ideal for emergencies. The proposed approach constructs the airspace as a constraints-embedded graph, compresses its dimensions, and applies a spectral clustering-enabled adaptive algorithm to generate collaborative airport groups and evenly distribute workloads among them. Under various traffic conditions, our experiments demonstrate a 50% reduction in workload imbalances. This research could ultimately form the basis for a recommendation system for optimized airspace configuration. Code available at https://github.com/KeFenge2022/GraphDAC.git
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Spatial–Temporal Graph Data Mining for IoT-Enabled Air Mobility Prediction

https://doi.org/10.1109/JIOT.2021.3090265

Jiang, Yushan; Niu, Shuteng; Zhang, Kai; Chen, Bowen; Xu, Chengtao; Liu, Dahai; Song, Houbing (June 2022, IEEE Internet of Things Journal)

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Zero-bias Deep Neural Network for Quickest RF Signal Surveillance

https://doi.org/10.1109/IPCCC51483.2021.9679426

Liu, Yongxin; Chen, Yingjie; Wang, Jian; Niu, Shuteng; Liu, Dahai; Song, Houbing (October 2021, 2021 IEEE International Performance, Computing, and Communications Conference (IPCCC))

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