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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Customer segmentation based on smart meter data analytics: Behavioral similarities with manual categorization for building types
Hidenori Komatsu, Osamu Kimura
Energy and Buildings (2023) Vol. 283, pp. 112831-112831
Closed Access | Times Cited: 13

Showing 13 citing articles:

Customer Segmentation Using Hierarchical Clustering
Areeba Afzal, Laiba Khan, Muhammad Zunnurain Hussain, et al.
2022 IEEE 7th International conference for Convergence in Technology (I2CT) (2024)
Closed Access | Times Cited: 5
Customer segmentation in the digital marketing using a Q-learning based differential evolution algorithm integrated with K-means clustering
G. Wang
PLoS ONE (2025) Vol. 20, Iss. 2, pp. e0318519-e0318519
Open Access
A Large-Scale Residential Load Dataset in a Southern Province of China
Bo Li, Ruotao Yu, Kaiye Gan, et al.
Scientific Data (2025) Vol. 12, Iss. 1
Open Access
Methods and attributes for customer-centric dynamic electricity tariff design: A review
Tasmeea Rahman, Mohammad Lutfi Othman, Samsul Bahari Mohd Noor, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 192, pp. 114228-114228
Closed Access | Times Cited: 9
A holistic time series-based energy benchmarking framework for applications in large stocks of buildings
Marco Savino Piscitelli, Rocco Giudice, Alfonso Capozzoli
Applied Energy (2023) Vol. 357, pp. 122550-122550
Open Access | Times Cited: 6
High-resolution electric power load data of an industrial park with multiple types of buildings in China
Kaile Zhou, Dingding Hu, Rong Hu, et al.
Scientific Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 4
Unsupervised Mixture Models on the Edge for Smart Energy Consumption Segmentation with Feature Saliency
Hussein Al–Bazzaz, Muhammad Azam, Manar Amayri, et al.
Sensors (2023) Vol. 23, Iss. 19, pp. 8296-8296
Open Access | Times Cited: 2
Identifying highly-valued bank customers with current accounts based on the frequency and amount of transactions
Samer Nofal
Heliyon (2024) Vol. 10, Iss. 13, pp. e33490-e33490
Open Access
Improving Customer Engagement via Segmentation Empowered by Machine Learning
P. D. Mahendhiran, Harini Manickam, Bavana Sadhanantham, et al.
Kalpa publications in computing (2024) Vol. 19, pp. 206-194
Open Access
A measurement error prediction framework for smart meters in typical regions
C. X. Yu, Ning Sun, Jianwei Gao, et al.
Measurement (2024) Vol. 242, pp. 116254-116254
Closed Access
A Data-Driven Analytic Approach for Demand Response of Residential Electricity Consumption
Hanguan Wen, Biyuan Lin, Guodong Huang, et al.
(2024), pp. 1342-1347
Closed Access
Degradation trend evaluation for smart meters under high dry heat natural environments
Jun Ma, Zhaosheng Teng, Qiu Tang, et al.
Measurement (2023) Vol. 220, pp. 113410-113410
Closed Access | Times Cited: 1
Data-Driven Classification for Residential Coincident Peak Demand Contributors Using Actual Power, Sociological, and Meteorological Data
Soroush Vahedi, Long Zhao, Nour Tanjim, et al.
IEEE Transactions on Industry Applications (2023) Vol. 60, Iss. 2, pp. 2443-2452
Closed Access | Times Cited: 1
Mapping top-two-floor corner coordinates to building strains in deep latent space
Jun Su Park, Seung Kyu Jang, Taehoon Hong, et al.
Journal of Building Engineering (2023) Vol. 82, pp. 108279-108279
Closed Access
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