Accurate short-term load forecasting is important for running power systems efficiently and managing smart grids. In this study, we present an improved Temporal Convolutional Network (TCN) model and compare eight optimization algorithms: Adam, AdaBelief, RAdam, Ranger, AdamP, NovoGrad, Adan, and SAM. We used hourly ele...
Hmeda Musbah, Abdussalam Mohamed, Hamed H. Aly· 2026 IEEE Canadian Atlantic...· 0 citations
This paper proposes an electromagnetic (EM) environment classification framework that enables unmanned aerial vehicles (UAVs) and robotic platforms to perceive EM conditions as structured environmental states rather than unmodeled noise or isolated sensor faults. A physics-inspired, imbalanced multi-class dataset with...
Abdussalam Mohamed, Hmeda Musbah, Hamed H. Aly· 2026 IEEE Canadian Atlantic...· 0 citations
A comfort-aware reinforcement learning (RL) framework is presented for intelligent indoor environment control in smart buildings. The system comprises three primary components: a data-driven comfort classifier, a lightweight indoor environment simulator, and a Deep Q-Network (DQN) control agent. A synthetic dataset, re...
Abdussalam Mohamed, Hmeda Najemeddin Musbah, Hamed H. Aly· 2026 IEEE Canadian Atlantic...· 0 citations
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