From Computing Statistics under Interval and Fuzzy Uncertainty to Practical Applications: Need to Propagate the Statistics through Data Processing

  • Hung T. Nguyen
  • Vladik Kreinovich
  • Berlin Wu
  • Gang Xiang
Part of the Studies in Computational Intelligence book series (SCI, volume 393)

Abstract

Need for data processing. In many areas of science and engineering, we are interested in a quantity y which is difficult (or even impossible) to measure directly. For example, it is difficult to directly measure the distance to a faraway star or the amount of oil in an oil well. To estimate this quantity, we can:
  • measure auxiliary easier-to-measure (or to estimate) quantities x1,..., x n which are related to y by a known dependence y = f(x1,..., x n ), and then

  • use the results \(\tilde{x}_1,..., \tilde{x}_n\) of measuring (or estimating) x i to compute the estimate \(\tilde{y} = f(\tilde{x}_1,..., \tilde{x}_n\)) for y.

Keywords

Statistical Characteristic Seismic Wave Partial Information Linear Inequality General Data Processing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hung T. Nguyen
    • Vladik Kreinovich
      • Berlin Wu
        • Gang Xiang

          There are no affiliations available

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