Unmanned aerial vehicle swarm-assisted reliable federated learning for traffic flow prediction
Authors:
- Man ZhouMZMan Zhou
- Lansheng HanLHLansheng Han
- Yangyang GengYGYangyang Geng
- 3 April 2025
- journal article
- Published by Elsevier in Future Generation Computer Systems
- Vol. 170
Abstract
No abstract availableFunding Information
- National Natural Science Foundation of China (62302138)
This publication has 19 references indexed in Scilit:
- Minimizing Delay in UAV-Aided Federated Learning for IoT Applications With Straggling DevicesIEEE Open Journal of the Communications Society, 2024
- Performance Improvement in UAV Communication Systems With Uncertain Solar Energy SupplyIEEE Internet of Things Journal, 2023
- FedAGCN: A traffic flow prediction framework based on federated learning and Asynchronous Graph Convolutional NetworkApplied Soft Computing, 2023
- An Interrelated Imitation Learning Method for Heterogeneous Drone Swarm CoordinationIEEE Transactions on Emerging Topics in Computing, 2022
- A UAV-Assisted Search and Localization Strategy in Non-Line-of-Sight ScenariosIEEE Internet of Things Journal, 2022
- Incentive Mechanisms for Federated Learning: From Economic and Game Theoretic PerspectiveIEEE Transactions on Cognitive Communications and Networking, 2022
- Age of Information in Energy Harvesting Aided Massive Multiple Access NetworksIEEE Journal on Selected Areas in Communications, 2022
- SP2F: A secured privacy-preserving framework for smart agricultural Unmanned Aerial VehiclesComputer Networks, 2021
- A review of applications in federated learningComputers & Industrial Engineering, 2020
- A hierarchical temporal attention-based LSTM encoder-decoder model for individual mobility predictionNeurocomputing, 2020