Inventions, Volume 5, Issue 4 (December 2020) – 14 articles
Cover Story (view full-size image): Toward effective energy monitoring, this study presents an event-based non-intrusive load monitoring approach assisted by feature selection and ensemble machine learning techniques. To evaluate and validate the proposed approach, comprehensive digital simulations are carried out on real-world low sampling, 1/60 Hz, i.e., 1-minute interval measurements, load data. Based on the presented study and corresponding analysis of the results, it is concluded that the proposed approach generalizes well to the unseen testing data and yields a promising performance in terms of non-invasive load inference. View this paper
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