Computing under Interval Uncertainty: Traditional Approach Based on Uniform Distributions

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

Abstract

Traditional statistical approach: main idea. In the case of interval uncertainty, we only know the intervals, we do not know the probability distributions on these intervals. The traditional statistical approach to situations in which we have several alternatives with unknown probabilities is to use Laplace Principle of Indifference, according to which,

  • if we have several possible alternatives,

  • and we have no information about the probability of different alternatives,

  • we assume all these probabilities to be equal.

Keywords

Uniform Distribution Probability Density Function Lagrange Multiplier Central Limit Theorem Engineering Approach 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

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

          There are no affiliations available

          Personalised recommendations