{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T20:06:45Z","timestamp":1784318805297,"version":"3.55.0"},"reference-count":41,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T00:00:00Z","timestamp":1635724800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51907024"],"award-info":[{"award-number":["51907024"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>As a pivotal technological foundation for smart home implementation, non-intrusive load monitoring is emerging as a widely recognized and popular technology to replace the sensors or sockets networks for the detailed household appliance monitoring. In this paper, a probability model framed ensemble method is proposed for the target of robust appliance monitoring. Firstly, the non-intrusive load disaggregation-oriented ensemble architecture is presented. Then, dictionary learning model is utilized to formulate the individual classifier, while the sparse coding-based approach is capable of providing multiple solutions under greedy mechanism. Furthermore, a fully probabilistic model is established for combined classifier, where the candidate solutions are all labelled with probability scores and evaluated via two-stage decision-making. The proposed method is tested on both low-voltage network simulator platform and field measurement datasets, and the results show that the proposed ensemble method always guarantees an enhancement on the performance of non-intrusive load disaggregation. Besides, the proposed approach shows high flexibility and scalability in classification model selection. Therefore, by initializing the architecture and approach of ensemble method-based NILM, this work plays a pioneer role in using ensemble method to improve the robustness and reliability of non-intrusive appliance monitoring.<\/jats:p>","DOI":"10.3390\/s21217272","type":"journal-article","created":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T22:24:22Z","timestamp":1635805462000},"page":"7272","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Toward Robust Non-Intrusive Load Monitoring via Probability Model Framed Ensemble Method"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0823-5141","authenticated-orcid":false,"given":"Yu","family":"Liu","sequence":"first","affiliation":[{"name":"School of Electrical Engineering, Southeast University, Nanjing 210096, China"},{"name":"Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment, Nanjing 210018, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5913-0278","authenticated-orcid":false,"given":"Yan","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Southeast University, Nanjing 210096, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Hong","sequence":"additional","affiliation":[{"name":"State Grid Lianyungang Power Supply Company, Lianyungang 222000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qianyun","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Southeast University, Nanjing 210096, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shan","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Southeast University, Nanjing 210096, China"},{"name":"Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment, Nanjing 210018, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xueliang","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Southeast University, Nanjing 210096, China"},{"name":"Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment, Nanjing 210018, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.jclepro.2012.12.012","article-title":"An advanced energy management framework to promote energy awareness","volume":"43","author":"Vikhorev","year":"2013","journal-title":"J. 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