Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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The Estimation of Theoretical Semivariogram Adapting Genetic Algorithm for Kriging

  • Ryu, Je-Seon (Center of Innovative Design Optimization Technology, Hanyang University) ;
  • Park, Young-Sun (The Research Institute of Natural Science, Hanyang University) ;
  • Cha, Kyung-Joon (Department of Mathematics, Hanyang University)
  • Published : 2004.08.01
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Abstract

In order to use Kriging, one has to estimate three parameters(nugget, sill and range) of semivariogram, which shows the relationship in the given two sites. A visual fit of the semivariogram parameters to a few standard models is widely used. But, it does not give the suitable results and not provide the automated process of Kriging. The gradient based nonlinear least squares is another choices to estimate three parameters, but it has some problems such as initial value problem. In this paper, we suggest the genetic algorithm as a compatible alternative method to solve the above mentioned problem. Finally, we estimate three parameters of semivariogram of rain-fall by adapting the genetic algorithm, compute Kriging estimate and conclude its effectiveness and compatibility.

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