A Study on the Use of Kriging Models to Approximate Deterministic Computer Models
作者： Jay D. Martin , Timothy W. Simpson
DOI: 10.1115/DETC2003/DAC-48762
关键词: Mathematical optimization 、 Variogram 、 Maximum likelihood 、 Kriging 、 Applied mathematics 、 Model parameter 、 Global optimization 、 Computer experiment 、 Mathematics
摘要: The use of kriging models for approximation and global optimization has been steadily on the rise in past decade. standard approach used Design Analysis Computer Experiments (DACE) is to an Ordinary model approximate a deterministic computer model. Universal Detrended are two alternative types models. In this paper, description basics given, highlighting similarities differences between these three different underlying assumptions behind each. A comparative study then presented using six test problems. methods Maximum Likelihood Estimation (MLE) Cross-Validation (CV) parameter estimation compared types. one-dimension problem first visualize order show applications higher dimensions, four two-dimension 5-dimension also given.Copyright © 2003 by ASME
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