{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:27:14Z","timestamp":1740202034164,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"abstract":"<jats:p>Investigated here is a non-intrusive decomposition algorithm based on residential load signal separation, which established on non - intrusive load model by harmonic analysis of load steady - state current signal, and columned matrix equations by the harmonic component of a mixed signal and the harmonic component of a single signal. The equations are used as objective functions for load decomposition, and the least squares algorithm and the non-negative least squares algorithm are used to solve the global optimal solution of the objective function to get involved in the mixing of the various current signals and achieve the purpose of load de-composition. The simulation results demonstrate that the non-negative least squares algorithm is used to solve the equations with a higher load recognition accuracy than the least squares algorithm.<\/jats:p>","DOI":"10.3233\/978-1-61499-828-0-447","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:27:05Z","timestamp":1740133625000},"source":"Crossref","is-referenced-by-count":0,"title":["A Non-Intrusive Decomposition Algorithm Based On Residential Load Signal Separation"],"prefix":"10.3233","author":[{"family":"Han Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Qi Bing","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining III"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:59:23Z","timestamp":1740135563000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-827-3&spage=447&doi=10.3233\/978-1-61499-828-0-447"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-828-0-447","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2017]]}}}