Statistical Modeling of Separator Processes - An Application of Gaussian Processes with Bayesian Optimization
The separator is a machine with many applications, commonly used to separate liquids or solids into components with different density. Each application demands its own unique set of process parameters to achieve optimal results. Often the procedure of finding the best process parameters is conducted empirically, which can be very time consuming. This thesis aims to address this problem by providin