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Sequence-to-Sequence Model with Transformer-based Attention Mechanism and Temporal Pooling for Non-Intrusive Load Monitoring
This paper presents a novel Sequence-to-Sequence (Seq2Seq) model based on a transformer-based attention mechanism and temporal pooling for Non-Intrusive Load Monitoring (NILM) of smart buildings.
Non-Intrusive Load Monitoring (NILM) using Deep Neural Networks: A Review
Various methods, including machine learning and deep learning, have been used to implement and improve NILM algorithms.
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