Boosting short term electric load forecasting of high & medium voltage substations with visibility graphs and graph neural networks

N Giamarelos, EN Zois - Sustainable Energy, Grids and Networks, 2024 - Elsevier
Modern power grids are faced with a series of challenges, such as the ever-increasing
demand for renewable energy sources, extensive urbanization, climate and energy crisis …

[HTML][HTML] Software-defined network-based proactive routing strategy in smart power grids using graph neural network and reinforcement learning

MA Islam, M Ismail, R Atat, O Boyaci… - E-Prime-Advances in …, 2023 - Elsevier
Smart power grid relies on sensors and actuators to provide continuous monitoring and
precise control functions. Two types of data and command packets are associated with such …

Software-Defined Networking Based Resilient Proactive Routing in Smart Grids Using Graph Neural Networks and Deep Q-Networks

MA Islam, R Atat, M Ismail - IEEE Access, 2024 - ieeexplore.ieee.org
The enhanced functionality of the smart grid depends on the robust interconnection between
its physical and cyber-layer components. Two distinct categories of control data packets …

Enhancing Accuracy of Diabetic Retinopathy Detection Using a Hybrid Approach with the Fusion of Inceptionv3 and a Stacking Ensemble Learner

IA Taifa, T Islam, MA Islam, MME Noor… - … University Journal of …, 2024 - banglajol.info
Diabetic retinopathy (DR) is a severe global problem that affects millions of people
worldwide and gets worse over time. If left untreated, DR can lead to blindness. Early and …

Resilient Proactive Routing in Smart Power Grids

MA Islam - 2023 - search.proquest.com
The smart grid represents a significant advance over the traditional power grid. It depends
on the pervasive deployment of field devices (sensors and actuators) that enable continuous …