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References from Smart grid security: A deep neural network model to detect and mitigate electricity theft. Local targets link to admitted publications; unresolved targets remain external evidence.
A novel power theft and data breach detection technique for low-voltage distribution networks
10.1016/j.epsr.2025.111503 · 2025 · External reference
Multimodal selective state space model-based time series classification for electricity theft detection
10.1016/j.eswa.2025.127364 · 2025 · External reference
Electricity theft detection using deep reinforcement learning in smart power grids
10.1109/access.2023.3284681 · 2023 · External reference
An efficient electricity theft detection based on deep learning
10.1038/s41598-025-93140-z · 2025 · External reference
A two stage approach to electricity theft detection in AMI using deep learning
10.1016/j.ijepes.2023.109088 · 2023 · External reference
Electricity theft detection based on contrastive learning and non-intrusive load monitoring
10.1109/tsg.2023.3263219 · 2023 · External reference
The determinants of electricity theft: An empirical analysis of Indian states
10.1016/j.enpol.2016.02.048 · 2016 · External reference
Unresolved reference
2022 · External reference
Smart grid security: An effective hybrid CNN-based approach for detecting energy theft using consumption patterns
10.3390/s24041148 · 2024 · External reference
A novel feature engineered-CatBoost-based supervised machine learning framework for electricity theft detection
10.1016/j.egyr.2021.07.008 · 2021 · External reference
Electricity theft detection in smart grid using machine learning
10.3389/fenrg.2024.1383090 · 2024 · External reference
Feature extraction of risk group and electricity theft by using electrical profiles and physical data for classification in the power utilities
10.37936/ecti-cit.2024181.252738 · 2024 · External reference
Unresolved reference
2025 · External reference
Advanced electricity theft detection in smart metering systems via channel-correlation enhanced hierarchical kernel networks and matrix completion
10.1016/j.measurement.2025.117768 · 2025 · External reference
Electricity theft detection and prevention using technology-based models: A systematic literature review
10.3390/electricity5020017 · 2024 · External reference
Data-driven insights: Boosting algorithms to uncover electricity theft patterns in AMI
2025 · External reference
Electricity theft detection in smart grids based on deep neural network
10.1109/access.2022.3166146 · 2022 · External reference
Ensemble-learning-based decision support system for energy-theft detection in smart-grid environment
10.3390/en16041907 · 2023 · External reference
Adversarial measurements for convolutional neural network-based energy theft detection model in smart grid
10.1016/j.prime.2025.100909 · 2025 · External reference
A comprehensive review of recent developments in smart grid through renewable energy resources integration
10.1016/j.heliyon.2024.e25705 · 2024 · External reference
Detection and confirmation of electricity thefts in advanced metering infrastructure by long short-term memory and fuzzy inference system models
10.4314/njtd.v21i1.2294 · 2024 · External reference
Optimizing XGBoost for enhanced electrical theft detection: a fusion of particle Swarm and Jaya optimization techniques
2024 · External reference
Socio-economic predictors of electricity theft in developing countries: An Indian case study
10.1016/j.esd.2018.12.006 · 2019 · External reference
An ensemble deep convolutional neural network model for electricity theft detection in smart grids
2020 · External reference
Systematic review of energy theft practices and autonomous detection through artificial intelligence methods
10.1016/j.rser.2023.113544 · 2023 · External reference
Robust resampling and stacked learning models for electricity theft detection in smart grid
10.1016/j.egyr.2024.12.041 · 2025 · External reference
PE-DOCC: A novel periodicity-enhanced deep one-class classification framework for electricity theft detection
10.3390/app15042193 · 2025 · External reference
ETD-ConvLSTM: A deep learning approach for electricity theft detection in smart grids
10.1109/tifs.2023.3265884 · 2023 · External reference
Detection methods in smart meters for electricity thefts: A survey
2022 · External reference
Theft detection dataset for benchmarking and machine learning based classification in a smart grid environment
10.1016/j.jksuci.2022.05.007 · 2023 · External reference
