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A review of electric load classification in smart grid environment
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“Using ML, we can model and cluster individuals based on their climate knowledge, preferences, demographics, and consumption characteristics (e.g., [66,116,166,261,861]), and thus predict who will be most amenable to new technologies and sustainable behavior change.”
From Tackling climate change with machine learning (2023) · cites this paper as [861]
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Metadata
- Authors
- Zhou, K.-L., Yang, S.-L., & Shen, C.
- Affiliations
- Hefei University of Technology (CN)
- ORCID
- Shen, Chao
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2013-08
- Volume
- 24
- Pages
- 103-110
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W2171208762
- Cited by
- 254
- References
- 72
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 13 · 2023: 19 · 2022: 28 · 2021: 30 · 2020: 28 · 2019: 31 · 2018: 28 · 2017: 18 · 2016: 18 · 2015: 18 · 2014: 8 · 2013: 1
- FWCI
- 9.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Renewable and Sustainable Energy Reviews (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Energy Load and Power Forecasting
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid and Power Systems
- Keywords
- smart grid, clustering algorithms, bad data detection, load forecasting, tariff setting, fuzzy c-means clustering
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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