This paper explores the performance evaluation of player performance prediction models using various data mining techniques, focusing on the application of machine learning algorithms to predict individual and team performance in sports. The study compares the effectiveness of multiple data mining methods, including Random Forest, Support Vector Machines (SVM), and Neural Networks, in predicting key…
This project explores the development of AI-powered Virtual Reality (VR) and Augmented Reality (AR) systems to teach social skills to individuals with Autism Spectrum Disorder (ASD), utilizing the Proximal Policy Optimization (PPO) algorithm for reinforcement learning. Social communication challenges are central to ASD, and traditional interventions may not offer the flexibility or scalability needed for…
While on-court performance is crucial in badminton, off-court factors significantly influence an athlete’s overall performance. This study aims to investigate the impact of these often-overlooked factors on badminton players. Through a comprehensive literature review, we explore the influence of psychological, physiological, socioeconomic, and lifestyle factors on player performance. The study highlights the importance of mental…