A new AI model learns to "think" longer on hard problems, achieving more robust reasoning and better generalization to novel, unseen tasks.

This paper presents an AI-driven day-ahead optimal scheduling approach for a grid-connected AC microgrid with a solar panel and a battery energy storage system. Genetic Algorithm generates demand ...

Evolutionary intelligent algorithms and machine learning methods have shown merits in dealing with complex optimization problems. Therefore, this issue aims to provide a platform for such forum to ...

Optimize off-grid hybrid microgrid sizing for reliable power supply using enhanced Genetic Algorithm. Case study in Nigeria. Compare results with Brute Force and standard GA methods.