Train Station Parking Approach Based on Fuzzy Reinforcement Learning Algorithms

Train station parking (TSP) accuracy is important to enhance the efficiency of train operation and the safety of passengers for urban rail transit, while TSP is always subject to a series of uncertain factors. To increase the parking accuracy, robustness and self-learning ability, we propose a new t...

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Veröffentlicht in:	IEEE International Conference on Control and Automation (Print) S. 1411 - 1416
Hauptverfasser:	Yin, Jiateng, Su, Shuai, Li, Kaicheng, Tang, Tao
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.07.2019
Schlagworte:	Adaptation models Computational modeling fuzzy function Q-learning Rails Reinforcement learning Resistance Safety Silicon Train station parking
ISSN:	1948-3457
Online-Zugang:	Volltext
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