IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i19p3015-d1487073.html
   My bibliography  Save this article

Three-Valued Concept Analysis for 2 R Formal Contexts

Author

Listed:
  • Taisheng Zeng

    (Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China
    Fujian Provincial Key Laboratory of Data-Intensive Computing, Quanzhou 362000, China
    Fujian University Laboratory of Intelligent Computing and Information Processing, Quanzhou 362000, China)

  • Huilai Zhi

    (Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China
    Fujian Provincial Key Laboratory of Data-Intensive Computing, Quanzhou 362000, China
    Fujian University Laboratory of Intelligent Computing and Information Processing, Quanzhou 362000, China)

  • Yinan Li

    (Big Data Institute, Central South University, Changsha 410075, China)

  • Daxin Zhu

    (Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China
    Fujian Provincial Key Laboratory of Data-Intensive Computing, Quanzhou 362000, China
    Fujian University Laboratory of Intelligent Computing and Information Processing, Quanzhou 362000, China)

  • Jianbing Xiahou

    (Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China
    Fujian Provincial Key Laboratory of Data-Intensive Computing, Quanzhou 362000, China
    Fujian University Laboratory of Intelligent Computing and Information Processing, Quanzhou 362000, China)

Abstract

Russian Roulette is a well-known cruel gambling game and its concepts and methods have been exploited in a lot of research fields for decades. However, abundant useful information contained in the process of Russian Roulette is seldom studied with a mathematical model with interpretability. To this end, we define the 2 R formal context to model Russian Roulette and carry out 3-valued concept analysis for 2 R formal contexts to mine useful information. At first, the uniqueness of 2 R formal contexts is discussed from a formal concept analysis viewpoint. And then we propose 3-valued 2 R concepts and discuss their properties and the connections with the basic 2 R concepts. Experimental analysis demonstrates that 3-valued 2 R concept lattices can show many more different details compared with basic 2 R concept lattices. Finally, a case study about a Chinese herbal medicine is introduced to demonstrate the feasibility of the proposed model.

Suggested Citation

  • Taisheng Zeng & Huilai Zhi & Yinan Li & Daxin Zhu & Jianbing Xiahou, 2024. "Three-Valued Concept Analysis for 2 R Formal Contexts," Mathematics, MDPI, vol. 12(19), pages 1-17, September.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:19:p:3015-:d:1487073
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/19/3015/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/12/19/3015/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fra̧ckiewicz, Piotr & Schmidt, Alexandre G.M., 2014. "N-person quantum Russian roulette," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 8-14.
    2. Junhua Hu & Dan Chen & Pei Liang, 2019. "A Novel Interval Three-Way Concept Lattice Model with Its Application in Medical Diagnosis," Mathematics, MDPI, vol. 7(1), pages 1-14, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wajid Ali & Tanzeela Shaheen & Iftikhar Ul Haq & Hamza Ghazanfar Toor & Tmader Alballa & Hamiden Abd El-Wahed Khalifa, 2023. "A Novel Interval-Valued Decision Theoretic Rough Set Model with Intuitionistic Fuzzy Numbers Based on Power Aggregation Operators and Their Application in Medical Diagnosis," Mathematics, MDPI, vol. 11(19), pages 1-18, October.
    2. Valentino Santucci & Alfredo Milani & Fabio Caraffini, 2019. "An Optimisation-Driven Prediction Method for Automated Diagnosis and Prognosis," Mathematics, MDPI, vol. 7(11), pages 1-20, November.

    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:gam:jmathe:v:12:y:2024:i:19:p:3015-:d:1487073. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.