A surrogate model is a model that approximates or mimics the behavior of a more complex, computationally expensive model. It can be used to quickly and efficiently evaluate the results and predictions of the more complex model. The surrogate model is typically created using statistical or machine learning techniques, based on a set of input-output data generated by the original model. The surrogate model can then be used for optimization, sensitivity analysis, or uncertainty quantification, among other purposes.
Publication date: