Hybrid processing of stochastic and subjective uncertainty data Metadata

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Title

  • Main Title Hybrid processing of stochastic and subjective uncertainty data

Creator

  • Author: Cooper, J.A.
    Creator Type: Personal
    Creator Info: Sandia National Labs., Albuquerque, NM (United States)
  • Author: Ferson, S.
    Creator Type: Personal
    Creator Info: Applied Biomathematics, Setauket, NY (United States)
  • Author: Ginzburg, L.
    Creator Type: Personal
    Creator Info: State Univ. of New York, Stony Brook, NY (United States)

Contributor

  • Sponsor: United States. Department of Energy.
    Contributor Type: Organization
    Contributor Info: USDOE, Washington, DC (United States)

Publisher

  • Name: Sandia National Laboratories
    Place of Publication: Albuquerque, New Mexico
    Additional Info: Sandia National Labs., Albuquerque, NM (United States)

Date

  • Creation: 1995-11-01

Language

  • English

Description

  • Content Description: Uncertainty analyses typically recognize separate stochastic and subjective sources of uncertainty, but do not systematically combine the two, although a large amount of data used in analyses is partly stochastic and partly subjective. We have developed methodology for mathematically combining stochastic and subjective data uncertainty, based on new ``hybrid number`` approaches. The methodology can be utilized in conjunction with various traditional techniques, such as PRA (probabilistic risk assessment) and risk analysis decision support. Hybrid numbers have been previously examined as a potential method to represent combinations of stochastic and subjective information, but mathematical processing has been impeded by the requirements inherent in the structure of the numbers, e.g., there was no known way to multiply hybrids. In this paper, we will demonstrate methods for calculating with hybrid numbers that avoid the difficulties. By formulating a hybrid number as a probability distribution that is only fuzzy known, or alternatively as a random distribution of fuzzy numbers, methods are demonstrated for the full suite of arithmetic operations, permitting complex mathematical calculations. It will be shown how information about relative subjectivity (the ratio of subjective to stochastic knowledge about a particular datum) can be incorporated. Techniques are also developed for conveying uncertainty information visually, so that the stochastic and subjective constituents of the uncertainty, as well as the ratio of knowledge about the two, are readily apparent. The techniques demonstrated have the capability to process uncertainty information for independent, uncorrelated data, and for some types of dependent and correlated data. Example applications are suggested, illustrative problems are worked, and graphical results are given.
  • Physical Description: 20 p.

Subject

  • Keyword: Probability
  • Keyword: Statistics
  • Keyword: Stochastic Processes
  • STI Subject Categories: 99 Mathematics, Computers, Information Science, Management, Law, Miscellaneous
  • Keyword: Fuzzy Logic
  • Keyword: Probabilistic Estimation
  • Keyword: Data Covariances

Source

  • Other Information: PBD: Nov 1995

Collection

  • Name: Office of Scientific & Technical Information Technical Reports
    Code: OSTI

Institution

  • Name: UNT Libraries Government Documents Department
    Code: UNTGD

Resource Type

  • Report

Format

  • Text

Identifier

  • Other: DE96003603
  • Report No.: SAND--95-2450
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/200708
  • Office of Scientific & Technical Information Report Number: 200708
  • Archival Resource Key: ark:/67531/metadc673112

Note

  • Display Note: OSTI as DE96003603