Examples

This section illustrates how to use the SMT algorithms.

• Use of Least Squares Surrogate Model
• Use of Gradient Enhanced Neural Network Model
• Use of Radial Basis Function
• Use of Inverse Distance Weighting
• Use of Regularized minimal-energy tensor-product splines
• Use of Second-order polynomial approximation
• Use of Kriging
• Use of KPLS
• Use of KPLSK
• Use of GEKPLS
• Use of Mixture of Experts
• Use of Multi-Fidelity Kriging
• Use of Multi-Fidelity Kriging Partial Least Squares
• Use of Multi-Fidelity Kriging Partial Least Squares K
• Use of Mixed Variable Kriging