Energy Theft Detection Model Based on VAE-GAN for Imbalanced Dataset
Energy theft causes a lot of economic losses every year. In the practical environment of energy theft detection, it is required to solve imbalanced data problem where normal user data are significantly larger than energy theft data. In this paper, a variational autoencoder-generative adversarial net...
Main Authors: | Youngghyu Sun, Jiyoung Lee, Soohyun Kim, Joonho Seon, Seongwoo Lee, Chanuk Kyeong, Jinyoung Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-01-01
|
Series: | Energies |
Subjects: | |
Online Access: | https://www.mdpi.com/1996-1073/16/3/1109 |
Similar Items
-
Comparative Evaluation of VAEs, VAE-GANs and AAEs for Anomaly Detection in Network Intrusion Data
by: Mahmoud Mohamed
Published: (2023-12-01) -
Dual Autoencoders Generative Adversarial Network for Imbalanced Classification Problem
by: Ensen Wu, et al.
Published: (2020-01-01) -
Machine Learning With Variational AutoEncoder for Imbalanced Datasets in Intrusion Detection
by: Ying-Dar Lin, et al.
Published: (2022-01-01) -
Dual-Encoder VAE-GAN With Spatiotemporal Features for Emotional EEG Data Augmentation
by: Chenxi Tian, et al.
Published: (2023-01-01) -
Electricity Theft Detection Method Based on Ensemble Learning and Prototype Learning
by: Xinwu Sun, et al.
Published: (2024-01-01)