High-Fidelity Digital Twin Data Models by Randomized Dynamic Mode Decomposition and Deep Learning
This research presents a new method for creating efficient digital twin data models by combining randomized dynamic mode decomposition and deep learning, which could improve accuracy and reduce computational costs in fluid dynamics simulations.