Non-intrusive load monitoring for led light classification: A data-driven machine learning approach
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In this study, we propose a novel approach using the oscillation characteristics of the RMS current as the input to machine learning models, combined with the confident learning technique. Using the oscillation characteristics obtained by taking a discrete Fourier transform (DFT) of the RMS current as model input, we aim to reduce the computational requirements of the machine learning models.
Nội dung trích xuất từ tài liệu:
Non-intrusive load monitoring for led light classification: A data-driven machine learning approach
Nội dung trích xuất từ tài liệu:
Non-intrusive load monitoring for led light classification: A data-driven machine learning approach
Tìm kiếm theo từ khóa liên quan:
Non-intrusive load monitoring LED operational state classification Discrete Fourier transform Confident learning Data-centric machine learning Machine learningGợi ý tài liệu liên quan:
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