FASTGNN: A Topological Information Protected Federated Learning Approach for Traffic Speed Forecasting
IEEE Transactions on Industrial Informatics(2021)
摘要
Federated learning has been applied to various tasks in intelligent transportation systems to protect data privacy through decentralized training schemes. The majority of the state-of-the-art models in intelligent transportation systems (ITS) are graph neural networks (GNN)-based for spatial information learning. When applying federated learning to the ITS tasks with GNN-based models, the existing...
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关键词
Forecasting,Organizations,Predictive models,Transportation,Data privacy,Data models,Roads
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