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- Xiaofeng, Li (1)
- Xiaoying, Zheng (1)
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- Dempster–Shafer evidence (1)
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Nowadays, the restriction of resources and the environment is very severe. A circular economy is the only way to sustainable development, but how this works still needs more exploration. The series of studies carried out by the author are described in detail in this book. |
Nowadays, the restriction of resources and the environment is very severe. A circular economy is the only way to sustainable development, but how this works still needs more exploration. The series of studies carried out by the author are described in detail in this book. |
Reliable mechanical fault diagnosis of high-voltage circuit breakers is important to ensure the safety of electric power systems. Recent fault diagnosis approaches are mostly based on a single classifier whose performance relies heavily on expert prior knowledge. In this study, we propose an improved Dempster–Shafer evidence theory fused echo state neural network, an ensemble classifier for fault diagnosis. Evidence credibility is calculated through the evidence deviation matrix and the segmented circle function and employed as credibility weights to rectify the raw evidence. Then, an improved Dempster–Shafer evidence fusion algorithm is proposed to fuse evidence from different echo state network modules and sensors. Unlike conventional classifiers, the proposed methodology consists... |
