• DocumentCode
    1754864
  • Title

    The mathematical theory of evidence and measurement uncertainty - Expression and combination of measurement results via the random-fuzzy variables

  • Author

    Salicone, Simona

  • Author_Institution
    Dept. of Electron., Inf., & Bioeng, Politec. di Milano, Milan, Italy
  • Volume
    17
  • Issue
    5
  • fYear
    2014
  • fDate
    Oct. 2014
  • Firstpage
    36
  • Lastpage
    44
  • Abstract
    In a previous paper [1], it was proved how total ignorance can be effectively represented, in Shafer´s theory of evidence [2], by a rectangular possibility distribution. In addition, it was shown how this concept can be usefully employed to mathematically represent situations that are often met in the measurement practice, especially in the industrial world [3]. The aim of this new paper is to show how possibility distributions can be effectively used to represent any kind of knowledge, from total ignorance to total evidence, and combine different contributions, if necessary.
  • Keywords
    measurement theory; measurement uncertainty; possibility theory; statistical distributions; mathematical theory of evidence; measurement practice; measurement uncertainty; rectangular possibility distribution; Mathematical analysis; Measurement uncertainty; Probability distribution; Systematics;
  • fLanguage
    English
  • Journal_Title
    Instrumentation & Measurement Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1094-6969
  • Type

    jour

  • DOI
    10.1109/MIM.2014.6912200
  • Filename
    6912200