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A novel multi-scale physics-informed neural network with enhanced reinforcement learning (MPINN-ERL) for bearing fault diagnosis under data scarcity and achieves competitive diagnostic accuracy.
Experimental results show that the proposed dynamic wavelet optimisation and hierarchical reinforcement learning method outperforms state-of-the-art methods in both performance and reliability.
Stable operation of photovoltaic (PV) cells is crucial for reliable and efficient electricity generation in power systems. However, their poor defect characterization, large size variation, and high background noise lead to low automatic identification accuracy. In this paper, a YOLO-based network with an efficient fea...
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