Abstract: This paper proposes a deep reinforcement learning (DRL)-based framework for distribution network reconfiguration (DNR). The objective of the proposed framework is to minimize power losses in ...
Abstract: Anomaly detection (AD) is typically regarded as an unsupervised learning task, where the training data either do not contain any anomalous samples or contain only a few unlabeled anomalous ...
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