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.
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Bardossy, A., Bogardi, I. & Kelly, W.E. Kriging with imprecise (fuzzy) variograms. I: Theory. Math Geol 22, 63–79 (1990). https://doi.org/10.1007/BF00890297
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DOI: https://doi.org/10.1007/BF00890297