Multi-Task Federated Learning for Traffic Prediction and Its Application to Route Planning
2021 IEEE Intelligent Vehicles Symposium (IV)(2021)
摘要
A novel multi-task federated learning (FL) framework is proposed in this paper to optimize the traffic prediction models without sharing the collected data among traffic stations. In particular, a divisive hierarchical clustering is first introduced to partition the collected traffic data at each station into different clusters. The FL is then implemented to collaboratively train the learning mode...
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关键词
Simulation,Roads,Distributed databases,Clustering algorithms,Training data,Predictive models,Prediction algorithms
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