Electric theft detection in advanced metering infrastructure using Jaya optimized combined Kernel‐Tree boosting classifier—A novel sequentially executed supervised machine learning approach

KTBoost: Combined Kernel and Tree Boosting

(2021) Fabio Sigrist   NEURAL PROCESSING LETTERS

Machine learning classification algorithms and anomaly detection in conventional meters and Tunisian electricity consumption large datasets

(2021) Simona-Vasilica Oprea et al.   COMPUTERS & ELECTRICAL ENGINEERING

Detection of false data cyber-attacks for the assessment of security in smart grid using deep learning

(2021) Sudhakar Sengan et al.   COMPUTERS & ELECTRICAL ENGINEERING

An adaptive synthesis to handle imbalanced big data with deep siamese network for electricity theft detection in smart grids

(2021) Nadeem Javaid et al.   JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING

Energy Theft Detection in an Edge Data Center Using Deep Learning

(2021) Guixue Cheng et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

Non-technical losses detection using missing values’ pattern and neural architecture search

(2021) Ke Fei et al.   INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Scientific papers citation analysis using textual features and SMOTE resampling techniques

(2021) Muhammad Umer et al.   PATTERN RECOGNITION LETTERS

Detection of Electricity Theft Behavior Based on Improved Synthetic Minority Oversampling Technique and Random Forest Classifier

(2020) Zhengwei Qu et al.   Energies

Effective Electricity Theft Detection in Power Distribution Grids Using an Adaptive Neuro Fuzzy Inference System

(2020) Konstantinos V. Blazakis et al.   Energies

An Efficient Boosted C5.0 Decision-Tree-Based Classification Approach for Detecting Non-Technical Losses in Power Utilities

(2020) Muhammad Salman Saeed et al.   Energies

A Grid as Smart as the Internet

(2020) Yanli Liu et al.   Engineering

RSMOTE: A self-adaptive robust SMOTE for imbalanced problems with label noise

(2020) Baiyun Chen et al.   INFORMATION SCIENCES

A novel unsupervised feature‐based approach for electricity theft detection using robust PCA and outlier removal clustering algorithm

(2020) Saddam Hussain et al.   International Transactions on Electrical Energy Systems

A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and opportunities

(2020) Sergio González et al.   Information Fusion

Ensemble machine learning models for the detection of energy theft

(2020) Sravan Kumar Gunturi et al.   ELECTRIC POWER SYSTEMS RESEARCH

Energy Theft Detection Using Gradient Boosting Theft Detector With Feature Engineering-Based Preprocessing

(2019) Rajiv Punmiya et al.   IEEE Transactions on Smart Grid

Electricity Theft Detection in Smart Grid Systems: A CNN-LSTM Based Approach

(2019) Md. Nazmul Hasan et al.   Energies

Ensemble Bagged Tree Based Classification for Reducing Non-Technical Losses in Multan Electric Power Company of Pakistan

(2019) Saeed et al.   Electronics

Review of non-technical loss detection methods

(2018) George M. Messinis et al.   ELECTRIC POWER SYSTEMS RESEARCH

Probabilistic Peak Load Estimation in Smart Cities Using Smart Meter Data

(2018) Mingyang Sun et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Wide and Deep Convolutional Neural Networks for Electricity-Theft Detection to Secure Smart Grids

(2018) Zibin Zheng et al.   IEEE Transactions on Industrial Informatics

NTL Detection in Electric Distribution Systems Using the Maximal Overlap Discrete Wavelet-Packet Transform and Random Undersampling Boosting

(2018) Nelson Fabian Avila et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Non-Technical Losses Reduction by Improving the Inspections Accuracy in a Power Utility

(2018) Juan Ignacio Guerrero et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Detection of Non-Technical Losses Using Smart Meter Data and Supervised Learning

(2018) Madalina-Mihaela Buzau et al.   IEEE Transactions on Smart Grid

Response to “Vulnerability and resistance in the United Kingdom's smart meter transition”

(2018) David Shipworth et al.   ENERGY POLICY

Detection of non-technical losses in smart meter data based on load curve profiling and time series analysis

(2017) Esther Villar-Rodriguez et al.   ENERGY

Detection of energy theft and defective smart meters in smart grids using linear regression

(2017) Sook-Chin Yip et al.   INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Random forest missing data algorithms

(2017) Fei Tang et al.   Statistical Analysis and Data Mining

Spatial-Temporal Estimation for Nontechnical Losses

(2016) Lucas Teles Faria et al.   IEEE TRANSACTIONS ON POWER DELIVERY

Clustering of Electricity Consumption Behavior Dynamics Toward Big Data Applications

(2016) Yi Wang et al.   IEEE Transactions on Smart Grid

Electricity Theft Detection in AMI Using Customers’ Consumption Patterns

(2016) Paria Jokar et al.   IEEE Transactions on Smart Grid

Fraud detection in registered electricity time series

(2015) Josif V. Spirić et al.   INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Missing value imputation using a fuzzy clustering-based EM approach

(2015) Md. Geaur Rahman et al.   KNOWLEDGE AND INFORMATION SYSTEMS

Using Smart Meter Data to Improve the Accuracy of Intraday Load Forecasting Considering Customer Behavior Similarities

(2015) Franklin L. Quilumba et al.   IEEE Transactions on Smart Grid

An Overview of the Smart Grid in Great Britain

(2015) Nick Jenkins et al.   Engineering

Improving Knowledge-Based Systems with statistical techniques, text mining, and neural networks for non-technical loss detection

(2014) Juan I. Guerrero et al.   KNOWLEDGE-BASED SYSTEMS

Non-Cooperative Game Model Applied to an Advanced Metering Infrastructure for Non-Technical Loss Screening in Micro-Distribution Systems

(2014) Chia-Hung Lin et al.   IEEE Transactions on Smart Grid

A novel algorithm for feature selection using Harmony Search and its application for non-technical losses detection

(2011) Caio C.O. Ramos et al.   COMPUTERS & ELECTRICAL ENGINEERING

Integrated expert system applied to the analysis of non-technical losses in power utilities

(2011) Carlos León et al.   EXPERT SYSTEMS WITH APPLICATIONS

Protecting Smart Grid Automation Systems Against Cyberattacks

(2011) Dong Wei et al.   IEEE Transactions on Smart Grid

A New Approach for Nontechnical Losses Detection Based on Optimum-Path Forest

(2010) Caio César Oba Ramos et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Nontechnical Loss Detection for Metered Customers in Power Utility Using Support Vector Machines

(2009) Jawad Nagi et al.   IEEE TRANSACTIONS ON POWER DELIVERY