To accurately diagnose faults in power transformers, this paper proposes a method for power transformer fault diagnosis that utilizes Kernel Principal Component Analysis (KPCA) and Random Forest (RF).

An improved variational quantum shadow learning (VQSL) method is presented for the fault diagnosis of transformers. Localized variational quantum circuits for shadow feature extraction and a fully ...

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An analysis of four different topologies to meet ATE SMU requirements with a final, the two-stage approach as the most ...