Abstract: In this contribution we investigate possibilities of using neural network classification methods for Non-Intrusive Load Monitoring (NILM) methods ...
Abstract—In this contribution we investigate possibilities of using neural network classification methods for Non-Intrusive. Load Monitoring (NILM) methods ...
Transfer Learning. Conference Paper. An Approach to NILM using image-based features and transfer learning. June 2023. DOI:10.1109/IWSSIP58668.2023.10180301.
Jun 26, 2023 · Abstract: In this contribution we investigate possibilities of using neural network classification methods for Non-Intrusive Load Monitoring ...
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The results of this study indicate that the approach of transfer learning with pre-trained CNNs works quite well for NILM, since all the best models achieved a ...
A non-intrusive load monitoring algorithm based on multiple ...
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This paper proposes a novel NILM method that accomplishes deep feature fusion and classifier model fusion by an improved Dempster–Shafer (D–S) evidence theory.
Jul 26, 2022 · In this paper, we propose a new method, coined IMG-NILM, that utilises convolutional neural networks (CNN) to disaggregate electricity data ...
Dec 2, 2023 · The NILM method collects power data by installing an intelligent acquisition module at the household end, and analyzes the collected data with ...
This paper also quantitatively evaluate the worth of these transfer learning approaches based on the similarity between the source and target domains. [PDF] ...
Another approach of using pre-trained models for NILM is to train a model on visual recognition tasks and the transfer the image feature extractor to the ...