Jul 11, 2021 · A novel multi-task federated learning (FL) framework is proposed in this paper to optimize the traffic prediction models without sharing the collected data ...
Simulation results showcase the prediction accuracy improvement of the proposed multi-task FL framework over two baseline schemes and show that, ...
Jul 11, 2021 · A novel multi-task federated learning (FL) framework is proposed in this paper to optimize the traffic prediction models without sharing the ...
... To improve travel efciency, Qu et al. developed a probabilistic network model to predict the probability and capacity of ride sharing at each location using ...
A novel multi-task federated learning (FL) framework is proposed in this paper to optimize the traffic prediction models without sharing the collected data ...
Cada uno ostenta una superficie de 7 500 m 2 , libre de estructuras portantes, lo que da más juego a la hora de cambiar su distribución y acondicionamiento.
Multi-Task Federated Learning for Traffic Prediction and Its Application to Route Planning. Tengchan Zeng, Jianlin Guo, Kyeong Jin Kim, Kieran Parsons ...
, "Multi-Task Federated Learning for Traffic Prediction and Its Application to Route Planning", IEEE Intelligent Vehicles Symposium, July 2021. BibTeX ...
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Mar 14, 2024 · In this paper, we present a comprehensive review of the application of FL in ITS, with a particular focus on three key scenarios.
We propose a multi-task federated learning model where vehicles simultaneously execute tasks. To jointly maximize the network utility and efficiency.