Computing Statistics under Fuzzy Uncertainty: Formulation of the Problem

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

Abstract

Need to process fuzzy uncertainty. In many practical situations, we only have expert estimates for the inputs x i . Sometimes, experts provide guaranteed bounds on the x i , and even the probabilities of different values within these bounds. However, such cases are rare. Usually, the experts’ opinions about the uncertainty of their estimates are described by (imprecise, “fuzzy”) words from natural language. For example, an expert can say that the value x i of the i-th quantity is approximately equal to 1.0, with an accuracy most probably of about 0.1.

Keywords

Real Number Membership Function Computing Statistics Expert Knowledge Input Quantity 
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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