Online Monitoring of Heterogeneous Partially Observable Data Streams Based on Q-Learning

With the rapid advances in Internet of Things (IoT) technology and computational infrastructure, heterogeneous data streams are becoming common in various manufacturing applications. Meanwhile, the resource constraints often restrict the full observability of data streams due to limited budget for d...

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Veröffentlicht in:	IEEE transactions on automation science and engineering 2024-06, p.1-16
Hauptverfasser:	Li, Haoqian, Ye, Honghan, Cheng, Jing-Ru C., Liu, Kaibo
Format:	Artikel
Sprache:	eng
Schlagworte:	Data acquisition Data categorization heterogeneity Layout mean shift detection Monitoring partial observations Process control Process monitoring Q-learning reinforcement learning Streams
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