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A Hybrid Deep Neural Network for Electricity Theft Detection Using Intelligent Antenna‐Based Smart Meters

https://doi.org/10.1155/2021/9933111
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s10287-018-0325-xopenalex-snapshot
Big data analytics: an aid to detection of non-technical losses in power utilities
inferredcites →https://doi.org/10.1007/s12652-019-01649-9openalex-snapshot
Performance analysis of machine learning classifiers for non-technical loss detection
inferredcites →https://doi.org/10.1016/j.compeleceng.2019.106458openalex-snapshot
Real-time anomaly detection based on long short-Term memory and Gaussian Mixture Model
inferredcites →https://doi.org/10.1016/j.heliyon.2018.e00938openalex-snapshot
State-of-the-art in artificial neural network applications: A survey
inferredcites →https://doi.org/10.1016/j.ijepes.2017.09.019openalex-snapshot
Identification of suspicious electricity customers
inferredcites →https://doi.org/10.1016/j.measurement.2020.107840openalex-snapshot
Monitoring technical losses to improve non-technical losses estimation and detection in LV distribution systems
inferredcites →https://doi.org/10.1016/j.seps.2020.100804openalex-snapshot
Analysis and short-term predictions of non-technical loss of electric power based on mixed effects models
inferredcites →https://doi.org/10.1049/iet-cps.2018.5050openalex-snapshot
Energy theft detection for AMI using principal component analysis based reconstructed data
inferredcites →https://doi.org/10.1109/access.2017.2763624openalex-snapshot
Towards Optimization of Metaheuristic Algorithms for IoT Enabled Smart Homes Targeting Balanced Demand and Supply of Energy
inferredcites →https://doi.org/10.1109/access.2019.2891315openalex-snapshot
Drift-Aware Methodology for Anomaly Detection in Smart Grid
inferredcites →https://doi.org/10.1109/access.2019.2962510openalex-snapshot
Performance Analysis of Different Types of Machine Learning Classifiers for Non-Technical Loss Detection
inferredcites →https://doi.org/10.1109/access.2020.3021613openalex-snapshot
Towards Real-Time Energy Management of Multi-Microgrid Using a Deep Convolution Neural Network and Cooperative Game Approach
inferredcites →https://doi.org/10.1109/access.2020.3042636openalex-snapshot
An Attention Guided Semi-Supervised Learning Mechanism to Detect Electricity Frauds in the Distribution Systems
inferredcites →https://doi.org/10.1109/access.2021.3056566openalex-snapshot
Towards Sustainable Energy Efficiency With Intelligent Electricity Theft Detection in Smart Grids Emphasising Enhanced Neural Networks
inferredcites →https://doi.org/10.1109/glocom.2016.7841630openalex-snapshot
Big Data Analytics for Price Forecasting in Smart Grids
inferredcites →https://doi.org/10.1109/iwcmc48107.2020.9148314openalex-snapshot
CNN and GRU based Deep Neural Network for Electricity Theft Detection to Secure Smart Grid
inferredcites →https://doi.org/10.1109/tbdata.2017.2723563openalex-snapshot
Robust Big Data Analytics for Electricity Price Forecasting in the Smart Grid
inferredcites →https://doi.org/10.1109/tii.2018.2873814openalex-snapshot
A Novel Combined Data-Driven Approach for Electricity Theft Detection
inferredcites →https://doi.org/10.1109/tim.2020.3048784openalex-snapshot
Electricity Theft Detection Base on Extreme Gradient Boosting in AMI
inferredcites →https://doi.org/10.1109/tpwrd.2020.2974132openalex-snapshot
Non-Technical Loss Identification by Using Data Analytics and Customer Smart Meters
inferredcites →https://doi.org/10.1109/tpwrs.2018.2853162openalex-snapshot
NTL Detection in Electric Distribution Systems Using the Maximal Overlap Discrete Wavelet-Packet Transform and Random Undersampling Boosting
inferredcites →https://doi.org/10.1109/tsg.2015.2425222openalex-snapshot
Electricity Theft Detection in AMI Using Customers’ Consumption Patterns
inferredcites →https://doi.org/10.1109/tsg.2016.2560801openalex-snapshot
On the Study of Commercial Losses in Brazil: A Binary Black Hole Algorithm for Theft Characterization
inferredcites →https://doi.org/10.1109/tsg.2020.2973681openalex-snapshot
Deep Learning Detection of Electricity Theft Cyber-Attacks in Renewable Distributed Generation
inferredcites →https://doi.org/10.1155/2018/5018053openalex-snapshot
Predicting Short‐Term Electricity Demand by Combining the Advantages of ARMA and XGBoost in Fog Computing Environment
inferredcites →https://doi.org/10.1155/2019/1734615openalex-snapshot
A Unified Framework for Behaviour Monitoring and Abnormality Detection for Smart Home
inferredcites →https://doi.org/10.1155/2020/8810393openalex-snapshot
Fault-Tolerant Privacy-Preserving Data Aggregation for Smart Grid
inferredcites →https://doi.org/10.1162/089976698300017197openalex-snapshot
Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms
inferredcites →https://doi.org/10.3390/app10093151openalex-snapshot
Detection of Non-Technical Losses Using SOSTLink and Bidirectional Gated Recurrent Unit to Secure Smart Meters
inferredcites →https://doi.org/10.3390/app10124378openalex-snapshot
LSTM and Bat-Based RUSBoost Approach for Electricity Theft Detection
inferredcites →https://doi.org/10.3390/electronics8080860openalex-snapshot
Ensemble Bagged Tree Based Classification for Reducing Non-Technical Losses in Multan Electric Power Company of Pakistan
inferredcites →https://doi.org/10.3390/en12173310openalex-snapshot
Electricity Theft Detection in Smart Grid Systems: A CNN-LSTM Based Approach
inferredcites →https://doi.org/10.3390/en12183452openalex-snapshot
Knowledge Embedded Semi-Supervised Deep Learning for Detecting Non-Technical Losses in the Smart Grid
inferredcites →https://doi.org/10.3390/en13082039openalex-snapshot
Detection of Electricity Theft Behavior Based on Improved Synthetic Minority Oversampling Technique and Random Forest Classifier
inferredcites →https://doi.org/10.3390/en13123110openalex-snapshot
Effective Electricity Theft Detection in Power Distribution Grids Using an Adaptive Neuro Fuzzy Inference System
inferredcites →https://doi.org/10.3390/en13215599openalex-snapshot
A Combined Deep Learning and Ensemble Learning Methodology to Avoid Electricity Theft in Smart Grids
inferredcites →https://doi.org/10.3390/su11226287openalex-snapshot
An Innovative Home Energy Management Model with Coordination among Appliances using Game Theory
inferredcites →https://doi.org/10.3390/su12198023openalex-snapshot
Electricity Theft Detection Using Supervised Learning Techniques on Smart Meter Data
inferredcites →https://doi.org/10.5555/1121924.1121932openalex-snapshot
Combined 5 2 cv F Test for Comparing Supervised Classification Learning Algorithms

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4755076openalex-extracted
Machine and Deep Learning Base Stacking Model Using Hybrid Class Imbalanced Technique for Electricity Theft Detection in Smart Grid
inferred← citeshttps://doi.org/10.1007/978-981-19-8445-7_1openalex-snapshot
A Secure and Efficient Heterogeneous Signcryption Scheme for IIoT
inferred← citeshttps://doi.org/10.1007/978-981-95-4821-7_1openalex-snapshot
A Review of Multi-source and Multi-modal Anomaly Data Detection for New Power Systems
inferred← citeshttps://doi.org/10.1007/s00202-024-02342-7openalex-snapshot
Electricity theft detection in IoT-based smart grids using a parameter-tuned bidirectional LSTM with pre-trained feature learning mechanism
inferred← citeshttps://doi.org/10.1007/s00521-023-08222-8openalex-snapshot
Empirical mode decomposition-based multi-scale spectral graph convolution network for abnormal electricity consumption detection
inferred← citeshttps://doi.org/10.1007/s11664-025-12527-wopenalex-snapshot
A Deep Learning Approach for Classifying the Efficiency of Dual-Band Wearable Antennas in Remote Healthcare
inferred← citeshttps://doi.org/10.1007/s11831-024-10137-zopenalex-snapshot
AI Techniques in Detection of NTLs: A Comprehensive Review
inferred← citeshttps://doi.org/10.1007/s41870-025-03083-xopenalex-snapshot
Explainable fraud detection in smart grids using enhanced deep learning approach
inferred← citeshttps://doi.org/10.1016/j.engappai.2024.108442openalex-snapshot
A self-decision ant colony clustering algorithm for electricity theft detection
inferred← citeshttps://doi.org/10.1016/j.esr.2025.101798openalex-snapshot
Combating electricity fraud: Employing hybrid learning and computer vision for sustainable energy management
inferred← citeshttps://doi.org/10.1016/j.heliyon.2024.e35167openalex-snapshot
Deep learning-based electricity theft prediction in non-smart grid environments
inferred← citeshttps://doi.org/10.1016/j.segan.2022.100833openalex-snapshot
Pattern-based and context-aware electricity theft detection in smart grid
inferred← citeshttps://doi.org/10.1038/s41598-026-39693-zopenalex-snapshot
A stacking ensemble with Pareto optimization for scalable electricity theft detection via hybrid data repair and lightweight deployment
inferred← citeshttps://doi.org/10.1049/rpg2.12846openalex-snapshot
A novel deep learning technique to detect electricity theft in smart grids using AlexNet
inferred← citeshttps://doi.org/10.1109/access.2021.3094226openalex-snapshot
Internet of Things and Synergic Deep Learning Based Biomedical Tongue Color Image Analysis for Disease Diagnosis and Classification
inferred← citeshttps://doi.org/10.1109/access.2022.3150016openalex-snapshot
AlexNet, AdaBoost and Artificial Bee Colony Based Hybrid Model for Electricity Theft Detection in Smart Grids
inferred← citeshttps://doi.org/10.1109/access.2022.3230952openalex-snapshot
Adaptive Data Balancing Method Using Stacking Ensemble Model and Its Application to Non-Technical Loss Detection in Smart Grids
inferred← citeshttps://doi.org/10.1109/access.2023.3238732openalex-snapshot
Security and Integrity Attacks in Named Data Networking: A Survey
inferred← citeshttps://doi.org/10.1109/access.2023.3326724openalex-snapshot
Smart Meters for Smart Energy: A Review of Business Intelligence Applications
inferred← citeshttps://doi.org/10.1109/access.2024.3358683openalex-snapshot
Electricity Theft Detection in Smart Grids Based on Omni-Scale CNN and AutoXGB
inferred← citeshttps://doi.org/10.1109/icairc68035.2025.11385253openalex-snapshot
AdaBoost-RF Electricity Theft Detection Method Based on Improved SSA
inferred← citeshttps://doi.org/10.1109/icirca65293.2025.11089641openalex-snapshot
A Hybrid Machine Learning Approach for Electricity Theft Detection and Demand Prediction
inferred← citeshttps://doi.org/10.1142/s0218126625501014openalex-snapshot
A Convolution Neural Network and Genetic Algorithm-Based Abnormity Detection Model for Cyber Attacks
inferred← citeshttps://doi.org/10.14445/23488379/ijeee-v10i2p104openalex-snapshot
CNN with BI-LSTM Electricity Theft Detection based on Modified Cheetah Optimization Algorithm in Deep Learning
inferred← citeshttps://doi.org/10.3390/electricity5020017openalex-snapshot
Electricity Theft Detection and Prevention Using Technology-Based Models: A Systematic Literature Review
inferred← citeshttps://doi.org/10.37394/232025.2024.6.27openalex-snapshot
Development of an Integrated AI Model Based on CNN-SVM for Electricity Theft Detection
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