Electricity theft detection in smart grid systems: A CNN-LSTM based approach

MN Hasan, RN Toma, AA Nahid, MMM Islam, JM Kim - Energies, 2019 - mdpi.com
Among an electricity provider's non-technical losses, electricity theft has the most severe and
dangerous effects. Fraudulent electricity consumption decreases the supply quality …

[HTML][HTML] Electricity-theft detection for smart grid security using smart meter data: A deep-CNN based approach

EU Haq, C Pei, R Zhang, H Jianjun, F Ahmad - Energy Reports, 2023 - Elsevier
Electricity theft has a considerable negative effect on energy suppliers and power
infrastructure, leading to non-technical losses and business losses. Power quality …

Hybrid-order representation learning for electricity theft detection

Y Zhu, Y Zhang, L Liu, Y Liu, G Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Electricity theft is the primary cause of electrical losses in power systems, which severely
harms the economic benefits of electricity providers and threatens the safety of the power …

A robust hybrid deep learning model for detection of non-technical losses to secure smart grids

F Shehzad, N Javaid, A Almogren, A Ahmed… - IEEE …, 2021 - ieeexplore.ieee.org
For dealing with the electricity theft detection in the smart grids, this article introduces a
hybrid deep learning model. The model tackles various issues such as class imbalance …

Attention-based DenseNet for pneumonia classification

K Wang, P Jiang, J Meng, X Jiang - Irbm, 2022 - Elsevier
Objective The structural complexity and uneven gray distribution of pneumonia images
seriously affect the accuracy of pneumonia classification. As DenseNet has the characteristic …

High-accuracy and adaptive fault diagnosis of high-speed train bogie using dense-squeeze network

Y Zhang, N Qin, D Huang, B Wu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As one of the most important systems of high-speed train (HST), bogie system matters when
it comes to the safety and reliability of HST operation. In order to strengthen feature …

Electricity theft detection with self-attention

P Finardi, I Campiotti, G Plensack, RD de Souza… - arXiv preprint arXiv …, 2020 - arxiv.org
In this work we propose a novel self-attention mechanism model to address electricity theft
detection on an imbalanced realistic dataset that presents a daily electricity consumption …

Electricity theft detection to reduce non-technical loss using support vector machine in smart grid

RN Toma, MN Hasan, AA Nahid… - 2019 1st International …, 2019 - ieeexplore.ieee.org
Among the various reason behind Non-technical losses in smart grid, losses due to
electricity theft have become major apprehension in power system industries. A significant …

A new electricity theft detection method using hybrid adaptive sampling and pipeline machine learning

AK Tripathi, AC Pandey, N Sharma - Multimedia Tools and Applications, 2024 - Springer
Electricity theft not only results in higher electricity costs for regular paying customers but is
also a safety threat to the public due to illegal power connections made for cheating. Many …

Neural-architecture-search-based multiobjective cognitive automation system

EK Wang, SP Xu, CM Chen, N Kumar - IEEE Systems Journal, 2020 - ieeexplore.ieee.org
Currently, deep-learning-based cognitive automation for decision-making in industrial
informatics is a new hot topic in the field of cognitive computing, among which multiobjective …