IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v51y2020i2p229-241.html
   My bibliography  Save this article

Location and scale fuzzy random variables

Author

Listed:
  • Gholamreza Hesamian
  • Mohamad Ghasem Akbari
  • Javad Zendehdel

Abstract

Several interpretations have been proposed so far for fuzzy random variables to describe imprecision and randomness. In this paper, a novel notion of fuzzy random variable was proposed to model fuzziness and randomness in a statistical procedure. For this purpose, a frequently used family of probability distributions called location and scale were first employed as the origin of randomness. Then, α-values of fuzzy numbers were combined with randomness to describe the fuzziness in the nature of the processes to produce a new concept of fuzzy random variable called location and scale fuzzy random variables. Then, some essential statistical features of the proposed fuzzy random variables including fuzzy cumulative distribution function, fuzzy expectation, exact variance and imprecise probability of an interval were discussed. The classical method of moment estimator was also developed to estimate the location and scale parameters. The developed technique was illustrated via several numerical evaluations. As an real-life application of the proposed fuzzy random variable, the reliability functions of k-out-of-n system and some reliability evaluation criteria were introduced and interpreted. Some numerical examples were also presented to illustrate the calculation of the proposed fuzzy system reliability criteria.

Suggested Citation

  • Gholamreza Hesamian & Mohamad Ghasem Akbari & Javad Zendehdel, 2020. "Location and scale fuzzy random variables," International Journal of Systems Science, Taylor & Francis Journals, vol. 51(2), pages 229-241, January.
  • Handle: RePEc:taf:tsysxx:v:51:y:2020:i:2:p:229-241
    DOI: 10.1080/00207721.2019.1701131
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2019.1701131
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207721.2019.1701131?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Abbas Parchami & Przemyslaw Grzegorzewski & Maciej Romaniuk, 2024. "Statistical simulations with LR random fuzzy numbers," Statistical Papers, Springer, vol. 65(6), pages 3583-3600, August.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tsysxx:v:51:y:2020:i:2:p:229-241. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TSYS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.