OPTIMIZING PERFORMANCE EVALUATION OF BADMINTON PLAYERS USING PROXIMAL POLICY OPTIMIZATION (PPO) ALGORITHM
Badminton performance evaluation has traditionally relied on subjective coaching assessments and basic statistical metrics, limiting scalability and real-time feedback. This study proposes a novel framework leveraging Proximal Policy Optimization (PPO)—a reinforcement learning (RL) algorithm—to automate and enhance player performance analysis through data-driven decisionmaking. By integrating multi-modal inputs (computer vision for shuttle tracking, feedback from players…
A Review of Data Mining Techniques for Enhancing Energy Efficiency in IoT Systems
The rapid proliferation of Internet of Things (IoT) technologies has led to an unprecedented surge in data generation and energy consumption, raising concerns about sustainability and operational efficiency. This review explores the role of data mining techniques in enhancing energy efficiency across various IoT applications. By analyzing and classifying key data mining methods such as…