Feature Construction and Calibration for Clustering Daily Load Curves from Smart-Meter Data
- Submitting institution
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University of Northumbria at Newcastle
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 22062938
- Type
- D - Journal article
- DOI
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10.1109/TII.2016.2528819
- Title of journal
- IEEE Transactions on Industrial Informatics
- Article number
- -
- First page
- 645
- Volume
- 12
- Issue
- 2
- ISSN
- 1551-3203
- Open access status
- Out of scope for open access requirements
- Month of publication
- February
- Year of publication
- 2016
- 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
-
3
- Research group(s)
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D - Computer Vision and Natural Computing (CVNC)
- Citation count
- 45
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work has gained new understanding to the relationship between users’ social demographic features and their energy consumption behaviours. It initiated collaborations with Narec Distributed Energy (https://www.narecde.co.uk/) and Energy Systems Catapult in Birmingham. This paper has been cited over 30 times by leading journals, including IEEE Transactions on Smart Grid, Energy Informatics, IEEE Trans. Industrial Informatics, and IEEE Transactions on Power Systems.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -