IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/9112586.html
   My bibliography  Save this article

Correlation Measures for Cubic m-Polar Fuzzy Sets with Applications

Author

Listed:
  • Harish Garg
  • Muhammad Riaz
  • Muhammad Abdullah Khokhar
  • Maryam Saba

Abstract

A cubic - polar fuzzy set (CmPFS) is a new hybrid extension of - polar fuzzy set and cubic set. A CmPFS is a robust model to express multipolar information in terms of fuzzy intervals representing membership grades and fuzzy numbers representing nonmembership grades. In this article, we explore some new operational laws of CmPFSs, produce some related results, and discuss their consequences. We propose relative informational coefficients and relative noninformational coefficients for CmPFSs. These coefficients are analyzed to investigate further properties of CmPFSs. Based on these coefficients, we introduce new correlation measures and their weighted versions for CmPFSs. The value of proposed correlation measures is symmetrical and lies between −1 and 1. Moreover, the applications of the proposed correlation in pattern recognition and medical diagnosis are developed. The feasibility and efficiency of suggested correlation measures is determined by respective illustrative examples.

Suggested Citation

  • Harish Garg & Muhammad Riaz & Muhammad Abdullah Khokhar & Maryam Saba, 2021. "Correlation Measures for Cubic m-Polar Fuzzy Sets with Applications," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-19, September.
    • Handle: RePEc:hin:jnlmpe:9112586
    DOI: 10.1155/2021/9112586
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2021/9112586.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2021/9112586.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2021/9112586?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
    ---><---

    Citations

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


    Cited by:

    1. Iftikhar Ul Haq & Tanzeela Shaheen & Wajid Ali & Hamza Toor & Tapan Senapati & Francesco Pilla & Sarbast Moslem, 2023. "Novel Fermatean Fuzzy Aczel–Alsina Model for Investment Strategy Selection," Mathematics, MDPI, vol. 11(14), pages 1-23, July.
    2. Felwa Abukhodair & Wafaa Alsaggaf & Amani Tariq Jamal & Sayed Abdel-Khalek & Romany F. Mansour, 2021. "An Intelligent Metaheuristic Binary Pigeon Optimization-Based Feature Selection and Big Data Classification in a MapReduce Environment," Mathematics, MDPI, vol. 9(20), pages 1-14, October.

    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:hin:jnlmpe:9112586. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    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.