Improving multi-state appliance classification by SE-DenseNet based on color encoding in non-intrusive load monitoring
Yinghua Han,
Zhiwei Dou,
Yu Zhao
et al.
Abstract:Non-intrusive load monitoring (NILM) is a technique that efficiently monitors appliances' operational status and energy consumption by utilizing voltage and current data, without intrusive measurements. In NILM, designing efficient classification models and building distinctive load features are crucial. However, due to its continuously variable load characteristics, multi-state load identification remains the most challenging problem in NILM. In this paper, we improve the encoding of the color V–I trajectory … Show more
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