Automatic Diagnosis of Microgrid Networks’ Power Device Faults Based on Stacked Denoising Autoencoders and Adaptive Affinity Propagation Clustering

<div>The 3-dimensional clustering results for training dataset A by using an SAE/SDAE with FCM/GK/GG. (a) SAE-FCM-A. (b) SAE-GK-A. (c) SAE-GG-A. (d) SDAE-FCM-A. (e) SDAE-GK-A. (f) SDAE-GG-A.</div>

Complexity

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Figure 11

Figure 11: Automatic Diagnosis of Microgrid Networks’ Power Device Faults Based on Stacked Denoising Autoencoders and Adaptive Affinity Propagation Clustering 

Figure 11 | Automatic Diagnosis of Microgrid Networks’ Power Device Faults Based on Stacked Denoising Autoencoders and Adaptive Affinity Propagation Clustering 