Related references
Note: Only part of the references are listed.Fault Coordination Control for Converter-Interfaced Sources Compatible With Distance Protection During Asymmetrical Faults
Zhe Yang et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2023)
Electricity Theft Detection Using Euclidean and Graph Convolutional Neural Networks
Wenlong Liao et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2023)
A Stacked Machine and Deep Learning-Based Approach for Analysing Electricity Theft in Smart Grids
Inam Ullah Khan et al.
IEEE TRANSACTIONS ON SMART GRID (2022)
Performance Analysis of Electricity Theft Detection for the Smart Grid: An Overview
Zhongzong Yan et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2022)
A Novel Unsupervised Data-Driven Method for Electricity Theft Detection in AMI Using Observer Meters
Ruobin Qi et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2022)
Ensemble machine learning models for the detection of energy theft
Sravan Kumar Gunturi et al.
ELECTRIC POWER SYSTEMS RESEARCH (2021)
Electricity Theft Detection in Power Consumption Data Based on Adaptive Tuning Recurrent Neural Network
Guoying Lin et al.
FRONTIERS IN ENERGY RESEARCH (2021)
An empirical survey of data augmentation for time series classification with neural networks
Brian Kenji Iwana et al.
PLOS ONE (2021)
Detecting False Data Injection Attacks Using Canonical Variate Analysis in Power Grid
Chao Pei et al.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING (2021)
Auto-encoder-based generative models for data augmentation on regression problems
Hiroshi Ohno
SOFT COMPUTING (2020)
Data Augmentation for Electricity Theft Detection Using Conditional Variational Auto-Encoder
Xuejiao Gong et al.
ENERGIES (2020)
ABSI: An Adaptive Binary Splitting Algorithm for Malicious Meter Inspection in Smart Grid
Xiaofang Xia et al.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2019)
Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges
Yi Wang et al.
IEEE TRANSACTIONS ON SMART GRID (2019)
A Physically Inspired Data-Driven Model for Electricity Theft Detection With Smart Meter Data
Yuanqi Gao et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2019)
Integration of residual network and convolutional neural network along with various activation functions and global pooling for time series classification
Xiaowu Zou et al.
NEUROCOMPUTING (2019)
Wide and Deep Convolutional Neural Networks for Electricity-Theft Detection to Secure Smart Grids
Zibin Zheng et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2018)
GAME-THEORETIC MODELS OF ELECTRICITY THEFT DETECTION IN SMART UTILITY NETWORKS PROVIDING NEW CAPABILITIES WITH ADVANCED METERING INFRASTRUCTURE
Saurabh Amin et al.
IEEE CONTROL SYSTEMS MAGAZINE (2015)