Dakota Reference Manual  Version 6.4
Large-Scale Engineering Optimization and Uncertainty Analysis
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domain_decomposition


Piecewise Domain Decomposition for Global Surrogate Models

Specification

Alias: none

Argument(s): none

Required/Optional Description of Group Dakota Keyword Dakota Keyword Description
Optional cell_type

Type of the Geometric Cells Used for the Piecewise Decomposition Option of Global Surrogates

Optional support_layers

Optional Number of Support Layers for the Piecewise Decomposition Option of Global Surrogates

Optional discontinuity_detection

Optional Discontinuity Detection Capability for the Piecewise Decomposition Option of Global Surrogates

Description

Typical regression techniques use all available sample points to build continuous approximations the underlying function.

An alternative option is to use piecewise decomposition to locally approximate the function at some point using a few sample points from its neighborhood only. This option currently supports Polynomial Regression, Gaussian Process (GP) Interpolation, and Radial Basis Functions (RBF) Regression. It requires a decomposition cell type (currently set to be Voronoi cells). Optional parameters are: the number of layers of neighbors used to solve the regression problem (default is one layer), and an optional discontinuity detection capability (identified by a user-input jump or gradient threshold).

The method can also make use of the gradient and Hessian information, if available. The user needs to specify the keyword user_derivatives.