Process parameter prediction using multivariant structural regression

摘要

Multivariant feature extraction is used for training volumes or 2D images, (real or synthetic) coupled to process (effective) values probably obtained from direct simulation. These features are coupled with machine learning/regression algorithms to make a predictive model for the effective property. This model can then be used on a real geometry of a sample for effective parameter prediction.