Surrogate Models

A surrogate model is a machine learning model that predicts certain performance criteria which allows for a faster analysis than if a simulation was used. Surrogate models can be especially useful when computationally intensive simulations are required or when multiple different simulations or evaluations are being run on the geometry. A surrogate model is trained on simulated data and once trained, it can predict the performance of a new input. There are various machine learning models that can be used for surrogate models which include decision trees, Bayesian networks, and neural networks.