Privacy-Preserving Traffic Flow Prediction: A Federated Learning Approach

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Strategic Coalition for Data Pricing in IoT Data Markets

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TST-Trans: A Transformer Network for Urban Traffic Flow Prediction

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Cellular Traffic Prediction via Byzantine-Robust Asynchronous Federated Learning

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AI-Enabled Learning Architecture Using Network Traffic Traces over IoT Network: A Comprehensive Review

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Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting

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A transferable federated learning approach for wind power prediction based on active privacy clustering and knowledge merge

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Ftmoe: a federated transfer model based on mixture-of-experts for heterogeneous image classification

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From biases to opportunities: leveraging Location-Based-Service (LBS) data for next-generation transportation planning

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Federated Approach for Privacy-Preserving Traffic Prediction Using Graph Convolutional Network

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Traffic Flow Prediction using Machine Learning Techniques - A Systematic Literature Review

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A Novel Long-Term Noise Prediction System Based on $\alpha$DTW-DCRNN Using Periodically Unaligned Spatiotemporal Distribution Sequences

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Privacy-Preserving Federated Recurrent Neural Networks

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MulticloudFL: Adaptive Federated Learning for Improving Forecasting Accuracy in Multi-Cloud Environments

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Multi-Participant Vertical Federated Learning Based Time Series Prediction

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Federated Learning Support for Cybersecurity: Fundamentals, Applications, and Opportunities

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Dynamic Incentive Design for Federated Learning Based on Consortium Blockchain Using a Stackelberg Game

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Federated office plug-load identification for building management systems

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Privacy-preserving federated learning for transportation mode prediction based on personal mobility data

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Privacy-Preserving Outsourcing of K-Means Clustering for Cloud-Device Collaborative Computing in Space-Air-Ground Integrated IoT

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An Efficient Group Federated Learning Framework for Large-Scale EEG-Based Driver Drowsiness Detection

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Byzantine-Robust Multimodal Federated Learning Framework for Intelligent Connected Vehicle

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A traffic flow prediction framework based on integrated federated learning and Recurrent Long short-term networks

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Federated Learning-based Power Control and Computing for Mobile Edge Computing System

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A Federated Mixed Logit Model for Personal Mobility Service in Autonomous Transportation Systems

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Traffic Flow Prediction Based on Federated Learning with Joint PCA Compression and Bayesian Optimization

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A Privacy-Preserving Deep Learning Scheme for Edge-enhanced Smart Homes

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Blockchain-FRL for Vehicular Lane Changing: Toward Traffic, Data, and Training Safety

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Deep Graph Embedding for IoT Botnet Traffic Detection

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Path Planning Strategy Based on Principal Component Federation for Multi-Agent in Connected Vehicles

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Federated Learning for Intelligent Transportation Systems: Use Cases, Open Challenges, and Opportunities

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PPSTSL: A Privacy-preserving Dynamic Spatio-temporal Graph Data Federated Split Learning for traffic forecasting

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HeteroSFL: Split Federated Learning With Heterogeneous Clients and Non-IID Data

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Traffic Flow Prediction Using Big Data and Geographic Information Systems: A Survey of Data Sources, Frameworks, Challenges, and Opportunities

Ahmed, S., Abdelhamid, Y., & Hefny, H. A. (2023) · International Journal of Computing and Digital Systems · doi:10.12785/ijcds/140147 · Cited by 7

Modified NSGA-II for solving Bi-objective support unit location problem to assist roadside traffic survey with multi-stages

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Joint Optimization of Fairness and Energy Efficiency in Zero-Trust Federated Learning for Consumer Internet of Things: A Lossy Communication Perspective

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Inference Load-Aware Orchestration for Hierarchical Federated Learning

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The Impact of Federated Learning on Urban Computing

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RUPT-FL: Robust Two-Layered Privacy-Preserving Federated Learning Framework With Unlinkability for IoV

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Leveraging Stack4Things for Federated Learning in Intelligent Cyber Physical Systems

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BoFL

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5G Traffic Forecasting using Federated Learning

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WKNN-FDCNN method for big data driven traffic flow prediction in ITS

Soni, R., Roy, P., & Nagwanshi, K. K. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16591-4 · Cited by 7

Federated learning with network pruning and rebirth for remaining useful life prediction of engineering systems

Chen, X., Chen, X., Wang, H., Lu, S., & Yan, R. (2023) · Manufacturing Letters · doi:10.1016/j.mfglet.2023.08.037 · Cited by 7

Fine-Tuned Personality Federated Learning for Graph Data

Xue, M., Zhou, Z., Jiao, P., & Tang, H. (2024) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2024.3356388 · Cited by 7

Neural Network Coding of Difference Updates for Efficient Distributed Learning Communication

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Privacy Preservation for the IoMT Using Federated Learning and Blockchain Technologies

Alalawi, S., Alalawi, M., & Alrae, R. (2024) · Lecture Notes in Networks and Systems · doi:10.1007/978-3-031-65522-7_62 · Cited by 6

Evaluating the Impact of Mobility on Differentially Private Federated Learning

Kim, E.-J., & Lee, E. (2024) · Applied Sciences · doi:10.3390/app14125245 · Cited by 6

CMBA-FL: Communication-mitigated and blockchain-assisted federated learning for traffic flow predictions

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Securing Federated Learning in IoT: A Survey of Attacks, Defenses, and Frameworks

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Deep Reinforcement Learning for Sustainable Urban Mobility: A Bibliometric and Empirical Review

Jamal, S., Siddiqui, F., Alam, M. A., Mursaleen, M., Zafar, S., & Naaz, S. (2026) · Sensors · doi:10.3390/s26020376 · Cited by 7

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Federated Spatial–Temporal Synchronous Graph Convolutional Network for Cross-City Traffic Prediction

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Fair and Robust Federated Learning via Decentralized and Adaptive Aggregation based on Blockchain

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Optimizing Urban Traffic Incident Prediction With Vertical Federated Learning: A Feature Selection Based Approach

Hussain, B., & Afzal, M. K. (2024) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2024.3487268 · Cited by 7

PEAR: privacy-preserving and effective aggregation for byzantine-robust federated learning in real-world scenarios

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Structured Process on FL for Big Data Analysis

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Using Homomorphic Proxy Re‐Encryption to Enhance Security and Privacy of Federated Learning‐Based Intelligent Connected Vehicles

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