Innovative DT Design

Innovative digital twin (DT) design focuses on creating accurate virtual replicas of physical systems to improve monitoring, control, and decision-making across various industries. Current research emphasizes developing robust modeling methodologies, incorporating deep learning techniques like policy gradient methods and convolutional neural networks, and employing sophisticated feature scaling techniques such as DTization for enhanced model performance. This work is significant for advancing predictive maintenance, optimizing complex systems, and improving the explainability and reliability of AI-driven applications, ultimately leading to increased efficiency and cost savings.