An Innovative synthesis of deep learning techniques (DCapsNet & DCOM) for generation electrical renewable energy from wind energy

From centralized grids to intelligent energy ecosystems: A privacy-preserving federated reinforcement learning architecture for autonomous renewable energy forecasting and surplus management

Privacy-preserving Photovoltaic Power Forecasting Using PCA-enhanced Federated LSTM Networks for Distributed Renewable Energy Systems

Whispers of the Wind: An Enhanced MLDD Model with Attention and Multi-Objective Optimization (MOGWO-PCA-GRU-Attention) for Ultra-Accurate Wind Power Forecasting

Pragmatic Fields of Artificial Intelligence (AI) and Artificial General Intelligence(AGI): A Comparative Analysis

An Adaptive, Physics-Guided Federated Multi-Agent Reinforcement Learning Framework for Proactive Air Pollution Mitigation