Predictive segmentation of energy consumers

Albert, Adrian; Maasoumy, Mehdi

doi:10.1016/j.apenergy.2016.05.128

Cited by 29Customer churn and segmentationData Mining and Machine Learning ApplicationsSmart Grid Energy Management

Predictive segmentation of energy consumers

Albert, Adrian, Maasoumy, Mehdi·2016·Applied Energy

DOI 10.1016/j.apenergy.2016.05.128

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Authors: Albert, A., & Maasoumy, M.
Corresponding author: Albert, Adrian
ORCID: Albert, Adrian
Maasoumy, Mehdi
Venue: Applied Energy
Publisher: Elsevier BV
Published: 2016-09
Volume: 177
Pages: 435-448
ISSN: 0306-2619 (ISSN-L)
DOI: 10.1016/j.apenergy.2016.05.128
OpenAlex: W4244411177
Cited by: 29
References: 35
Citations by year: 2026: 1 · 2025: 1 · 2024: 1 · 2023: 1 · 2022: 3 · 2021: 7 · 2020: 5 · 2019: 4 · 2018: 3 · 2017: 3
FWCI: 6.94
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: Applied Energy (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Topics: Social Sciences › Business, Management and Accounting › Marketing › Customer churn and segmentation
Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
Keywords: customer segmentation, program enrollment, energy consumption data, consumer demographics, interpretability, energy efficiency programs

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