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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:

Electricity theft detection in low-voltage stations based on similarity measure and DT-KSVM
Xiangyu Kong, Xin Zhao, Chao Liu, et al.
International Journal of Electrical Power & Energy Systems (2020) Vol. 125, pp. 106544-106544
Closed Access | Times Cited: 86

Showing 1-25 of 86 citing articles:

Performance Analysis of Electricity Theft Detection for the Smart Grid: An Overview
Zhongzong Yan, He Wen
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 71, pp. 1-28
Closed Access | Times Cited: 70
Electricity Theft Detection Method Based on Ensemble Learning and Prototype Learning
Xinwu Sun, Jiaxiang Hu, Zhenyuan Zhang, et al.
Journal of Modern Power Systems and Clean Energy (2024) Vol. 12, Iss. 1, pp. 213-224
Open Access | Times Cited: 11
Monitoring high-carbon industry enterprise emission in carbon market: A multi-trusted approach using externally available big data
Bixuan Gao, Xiangyu Kong, Gaohua Liu, et al.
Journal of Cleaner Production (2024) Vol. 466, pp. 142729-142729
Closed Access | Times Cited: 9
Contrastive Learning for Efficient Anomaly Detection in Electricity Load Data
Mohit Choubey, Rahul Kumar Chaurasiya, J. S. Yadav
Sustainable Energy Grids and Networks (2025), pp. 101639-101639
Closed Access | Times Cited: 1
Towards Efficient Energy Utilization Using Big Data Analytics in Smart Cities for Electricity Theft Detection
Arooj Arif, Turki Ali Alghamdi, Zahoor Ali Khan, et al.
Big Data Research (2021) Vol. 27, pp. 100285-100285
Closed Access | Times Cited: 51
Electricity theft detection using big data and genetic algorithm in electric power systems
Faisal Shehzad, Nadeem Javaid, Sheraz Aslam, et al.
Electric Power Systems Research (2022) Vol. 209, pp. 107975-107975
Closed Access | Times Cited: 32
Electricity theft detection based on hybrid random forest and weighted support vector data description
Qingyuan Cai, Peng Li, Ruchuan Wang
International Journal of Electrical Power & Energy Systems (2023) Vol. 153, pp. 109283-109283
Open Access | Times Cited: 19
A two stage approach to electricity theft detection in AMI using deep learning
Mahdi Emadaleslami, Mahmoud‐Reza Haghifam, Mansoureh Zangiabadi
International Journal of Electrical Power & Energy Systems (2023) Vol. 150, pp. 109088-109088
Closed Access | Times Cited: 17
A Robust Hybrid Deep Learning Model for Detection of Non-Technical Losses to Secure Smart Grids
Faisal Shehzad, Nadeem Javaid, Ahmad Almogren, et al.
IEEE Access (2021) Vol. 9, pp. 128663-128678
Open Access | Times Cited: 35
Big data analytics for identifying electricity theft using machine learning approaches in microgrids for smart communities
Arooj Arif, Nadeem Javaid, Abdulaziz Aldegheishem, et al.
Concurrency and Computation Practice and Experience (2021) Vol. 33, Iss. 17
Closed Access | Times Cited: 33
BiGRU-CNN Neural Network Applied to Electric Energy Theft Detection
Lucas Duarte Soares, Altamira de Souza Queiroz, Gloria P. López, et al.
Electronics (2022) Vol. 11, Iss. 5, pp. 693-693
Open Access | Times Cited: 28
Synthetic Theft Attacks and Long Short Term Memory-Based Preprocessing for Electricity Theft Detection Using Gated Recurrent Unit
Pamir, Nadeem Javaid, Saher Javaid, et al.
Energies (2022) Vol. 15, Iss. 8, pp. 2778-2778
Open Access | Times Cited: 26
A CNN-transformer hybrid approach for an intrusion detection system in advanced metering infrastructure
Ruizhe Yao, Ning Wang, Peng Chen, et al.
Multimedia Tools and Applications (2022) Vol. 82, Iss. 13, pp. 19463-19486
Closed Access | Times Cited: 25
Electricity Theft Detection Based on Contrastive Learning and Non-Intrusive Load Monitoring
Ang Gao, Fei Mei, Jianyong Zheng, et al.
IEEE Transactions on Smart Grid (2023) Vol. 14, Iss. 6, pp. 4565-4580
Closed Access | Times Cited: 14
Artificial Intelligence for Energy Theft Detection in Distribution Networks
Mileta Žarković, Goran Dobrić
Energies (2024) Vol. 17, Iss. 7, pp. 1580-1580
Open Access | Times Cited: 5
Non-technical losses detection using missing values’ pattern and neural architecture search
Fei Ke, Qi Li, Congcong Zhu
International Journal of Electrical Power & Energy Systems (2021) Vol. 134, pp. 107410-107410
Closed Access | Times Cited: 32
Data Augmentation Using BiWGAN, Feature Extraction and Classification by Hybrid 2DCNN and BiLSTM to Detect Non-Technical Losses in Smart Grids
Muhammad Asif, Orooj Nazeer, Nadeem Javaid, et al.
IEEE Access (2022) Vol. 10, pp. 27467-27483
Open Access | Times Cited: 21
A machine learning-based detection framework against intermittent electricity theft attack
Hongliang Fang, Jiang‐Wen Xiao, Yan‐Wu Wang
International Journal of Electrical Power & Energy Systems (2023) Vol. 150, pp. 109075-109075
Closed Access | Times Cited: 12
Enhancing anomaly detection accuracy and interpretability in low-quality and class imbalanced data: A comprehensive approach
Bixuan Gao, Xiangyu Kong, Shangze Li, et al.
Applied Energy (2023) Vol. 353, pp. 122157-122157
Closed Access | Times Cited: 12
A synergistic oversampling technique with differential evolution and safe level synthetic minority oversampling
Ahmet Cevahir Çınar
Applied Soft Computing (2025), pp. 112819-112819
Closed Access
PE-DOCC: A Novel Periodicity-Enhanced Deep One-Class Classification Framework for Electricity Theft Detection
Wu Zhi, Yufeng Wang
Applied Sciences (2025) Vol. 15, Iss. 4, pp. 2193-2193
Open Access
A critical review of technical case studies for electricity theft detection in smart grids: A new paradigm based transformative approach
Muhammad Sajid Iqbal, Shoaib Munawar, Muhammad Gufran Khan, et al.
Energy Conversion and Management X (2025), pp. 100965-100965
Open Access
Research on intelligent analysis and prediction of low-voltage causes in rural distribution networks based on deep learning
Wei Wang, Shuman Sun, Peng-Xuan Liu, et al.
International Journal of Low-Carbon Technologies (2025) Vol. 20, pp. 791-797
Open Access
Methodological Validation of Machine Learning Models for Non-Technical Loss Detection in Electric Power Systems: A Case Study in an Ecuadorian Electricity Distributor
Carlos Arias-Marín, Antonio Barragán-Escandón, Marco Toledo-Orozco, et al.
Applied Sciences (2025) Vol. 15, Iss. 7, pp. 3912-3912
Open Access
Non-Technical Losses Detection Using Autoencoder and Bidirectional Gated Recurrent Unit to Secure Smart Grids
Pamir, Nadeem Javaid, U. Qasim, et al.
IEEE Access (2022) Vol. 10, pp. 56863-56875
Open Access | Times Cited: 17
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