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Based upon the analysis of load signatures, this paper presents a nonintrusive load monitoring (NILM) technique. With a characterizing response associated with a transient energy signature, a reliable and accurate recognition result can be obtained. In this paper, artificial neural networks, in combination with turn-on transient energy analysis, are used to improve recognition accuracy and computational...
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