Browsing: CTGAN

The integration of artificial intelligence (AI) into adaptive and autonomous systems announces a new era for Industry 5.0. The concept emphasizes human-centric, sustainable, and intelligent industrial processes. This study presents a comprehensive framework that combines supervised machine learning and generative modelling to predict and synthesize load types in industrial energy consumption data. A TinyML achieved…