KSME International Journal

, Volume 16, Issue 5, pp 619–632 | Cite as

Kriging interpolation methods in geostatistics and DACE model

  • Je-Seon Ryu
  • Min-Soo Kim
  • Kyung-Joon Cha
  • Tae Hee Lee
  • Dong-Hoon Choi
Materials & Fracture · Solids & Structures · Dynamics & Control · Production & Design

Abstract

In recent study on design of experiments, the complicate metamodeling has been studied because defining exact model using computer simulation is expensive and time consuming. Thus, some designers often use approximate models, which express the relation between some inputs and outputs. In this paper, we review and compare the complicate metamodels, which are expressed by the interaction of various data through trying many physical experiments and running a computer simulation. The prediction model in this paper employs interpolation schemes known as ordinary kriging developed in the fields of spatial statistics and kriging in Design and Analysis of Computer Experiments (DACE) model. We will focus on describing the definitions, the prediction functions and the algorithms of two kriging methods, and assess the error measures of those by using some validation methods.

Key Words

Kriging Ordinary Kriging DACE Model Semivariogram Correlation Function BLUP 

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Copyright information

© The Korean Society of Mechanical Engineers (KSME) 2002

Authors and Affiliations

  • Je-Seon Ryu
    • 2
  • Min-Soo Kim
    • 1
  • Kyung-Joon Cha
    • 2
  • Tae Hee Lee
    • 3
  • Dong-Hoon Choi
    • 1
  1. 1.Center of Innovative Design Optimization TechnologyHanyang UniversitySeoulKorea
  2. 2.Department of MathematicsHanyang UniversitySeoulKorea
  3. 3.School of Mechanical EngineeringHanyang UniversitySeoulKorea

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