Deep learning for model correction of dynamical systems with data
scarcity
Deep learning for model correction of dynamical systems with data
scarcity
We present a deep learning framework for correcting existing dynamical system models utilizing only a scarce high-fidelity data set. In many practical situations, one has a low-fidelity model that can capture the dynamics reasonably well but lacks high resolution, due to the inherent limitation of the model and the complexity …