Non-Intrusive Load Monitoring Using Semi-Supervised Machine Learning and Wavelet Design

This paper presents a new approach based on semi-supervised machine learning and wavelet design applied to non-intrusive load monitoring. Co-training of two machine learning classifiers is used to automate the process of learning the load pattern after designing new wavelets. The numerical results demonstrating the effectiveness of the proposed approach are discussed and conclusions are drawn.