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  • fuzzy set theory  (2)
  • 1
    Electronic Resource
    Electronic Resource
    Kriging with imprecise (fuzzy) variograms. I: Theory (1990)
    Springer
    Mathematical geology 22 (1990), S. 63-79 
    Details
    ISSN: 1573-8868
    Keywords: kriging ; variogram ; fuzzy set theory ; prior information ; methodology
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract Imprecise variogram parameters are modeled with fuzzy set theory. The fit of a variogram model to experimental variograms is often subjective. The “accuracy” of the fit is modeled with imprecise variogram parameters. Measurement data often are insufficient to create “good” experimental variograms. In this case, prior knowledge and experience can contribute to determination of the variogram model parameters. A methodology for kriging with imprecise variogram parameters is developed. Both kriged values and estimation variances are calculated as fuzzy numbers and characterized by their membership functions. Besides estimation variance, the membership functions are used to create another uncertainty measure. This measure depends on both homogeneity and configuration of the data.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00890297
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    Paper (German National Licenses)
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  • 2
    Electronic Resource
    Electronic Resource
    Kriging with imprecise (fuzzy) variograms. II: Application (1990)
    Springer
    Mathematical geology 22 (1990), S. 81-94 
    Details
    ISSN: 1573-8868
    Keywords: application ; permeability prediction ; soil liner ; kriging ; variogram ; fuzzy set theory
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract The geostatistical analysis of soil liner permeability is based on 20 measurements and imprecise prior information on nugget effect, sill, and range of the unknown variogram. Using this information, membership functions for variogram parameters are assessed and the fuzzy variogram is constructed. Both kriging estimates and estimation variances are calculated as fuzzy numbers from the fuzzy variogram and data points. Contour maps are presented, indicating values of the kriged permeability and the estimation variance corresponding to selected membership values called levels.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00890298
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    Paper (German National Licenses)
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