Low-Complexity Non-Intrusive Load Monitoring Using Unsupervised Learning and Generalized Appliance Models
- Submitting institution
-
University of Salford, The
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 59446
- Type
- D - Journal article
- DOI
-
10.1109/TCE.2019.2891160
- Title of journal
- IEEE Transactions on Consumer Electronics
- Article number
- -
- First page
- 28
- Volume
- 65
- Issue
- 1
- ISSN
- 1558-4127
- Open access status
- Not compliant
- Month of publication
- January
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 21
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- -
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -