Apr 9, 2024 · In this paper, we propose using federated learning (FL)-based edge computing to train the ATO model without transmitting a large amount of data.
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Jun 26, 2024 · Automatic train operation (ATO) is a critical component of automatic train control (ATC) systems. The ATO automatically adjusts the speed of ...
Federated learning-based edge computing for automatic train operation in communication-based train control systems. https://doi.org/10.1007/s11227-024-06075 ...
Article "Federated learning-based edge computing for automatic train operation in communication-based train control systems" Detailed information of the ...
The ATO automatically adjusts the speed of trains, ensuring the safety of trains and increasing the passenger capacity of urban railway networks. The ...
Federated learning-based edge computing for automatic train operation in communication-based train control systems. Zhouhao Zhang; Hailin Jiang; Yang Li.
Federated Learning is a machine learning scheme in which a shared prediction model can be collaboratively learned by a number of distributed nodes using ...
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Collaborative Train and Edge Computing in Edge Intelligence Based Train Autonomous Operation Control Systems. IEEE Trans. Intell. Transp. Syst. 25(9): 11991 ...
Federated learning (FL) is a natural solution for massive user-owned devices in edge computing with distributed and private training data.
This paper provides an overview of the methods used in FL with a focus on edge devices with limited computational resources.