The results show that the Decision Tree model emerged as the top-performing algorithm, achieving an accuracy rate of 99.36 percent. Random Forest followed closely with 99.27 percent accuracy, while ...

Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...

Abstract: In the field of autonomous driving, safe and efficient decision-making through deep reinforcement learning remains a significant challenge. Existing methods often struggle to adapt to the ...

Abstract: Accurate wind power forecasting is crucial for efficient power grid operation with significant wind power integration. This study compares tree-based learning algorithms and advanced machine ...