Multi-Edge Graph Convolutional Networks for Power Systems
The exponential electrification of transportation has contributed to highly intermittent load
variations in the distribution grid. This uncertainty has raised challenges for distribution …
variations in the distribution grid. This uncertainty has raised challenges for distribution …
Detection of False Data Injection Attacks in Smart Microgrid using Deep Learning to Improve Classification Algorithms
H Shahinzadeh, GB Gharehpetian… - … on Smart-Green …, 2023 - ieeexplore.ieee.org
Detecting false data injection (FDI) attacks poses a significant challenge in smart microgrids.
Recently, classification algorithms have been employed to address this issue. However, the …
Recently, classification algorithms have been employed to address this issue. However, the …
Securing transportation web applications: An AI-driven approach to detect and mitigate SQL injection attacks
N Mohamed - Journal of Transportation Security, 2024 - Springer
Cybersecurity is a critical concern in the transportation sector, where web applications play a
pivotal role in managing essential services and sensitive data. Among the various cyber …
pivotal role in managing essential services and sensitive data. Among the various cyber …
A parallel approach for ultra-fast state estimation in large power system using graph partitioning theory
BK Sarmadi, AS Dobakhshari - Acta IMEKO, 2024 - acta.imeko.org
This paper introduces a novel approach for multi-area state estimation in large transmission
networks through the application of graph partitioning theory. By harnessing the eigenvalues …
networks through the application of graph partitioning theory. By harnessing the eigenvalues …
Recent Advances in Distribution System State Estimation Algorithms: from Model-based to Data-driven Approach
W Sulaimon, I Habiballah - 2023 - preprints.org
This article presents a review of the distribution system state estimation (DSSE) algorithms
from the model-based approach to the recent data-driven methodologies. The insufficient …
from the model-based approach to the recent data-driven methodologies. The insufficient …