IDEAS home Printed from https://ideas.repec.org/a/wut/journl/v32y2022i1p5-24id2642.html
   My bibliography  Save this article

Logarithmic similarity measures on Pythagorean fuzzy sets in admission process

Author

Listed:
  • Hari Darshan Arora
  • Anjali Naithani

Abstract

The intuitionistic fuzzy sets (IFSs) have a more significant contribution to describing and dealing with uncertainty. The intuitionistic fuzzy measure is a significant consideration in the field of IFSs theory. However, Pythagorean fuzzy sets (PFSs) are an extension of the IFSs. PFSs are more capable of modelling uncertainties than IFSs in real-world decision-making scenarios. The majority of PFSs research has concentrated on establishing decision-making frameworks. A similarity measure is a key concept which measures the closeness of PFSs. IFSs-based similarity measures have been proposed in the literature. This type of similarity measure, however, has a drawback since it cannot satisfy the axiomatic definition of similarity by offering counter-intuitive examples. For this study, a similarity based on logarithmic function for Pythagorean fuzzy sets (PFSs) is proposed as a solution to the problem. A decision-making approach is presented to ascertain the suitability of careers for aspirants. Additionally, numerical illustration is applied to determine the strength and validity of the proposed similarity measures. The application of the proposed similarity measures is also presented in this article. A comparison of the suggested measures with the existing ones is also demonstrated to ensure the reliability of the measures. The results show that the proposed similarity measures are efficient and reasonable from both numerical and realistic assessments.

Suggested Citation

  • Hari Darshan Arora & Anjali Naithani, 2022. "Logarithmic similarity measures on Pythagorean fuzzy sets in admission process," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 32(1), pages 5-24.
  • Handle: RePEc:wut:journl:v:32:y:2022:i:1:p:5-24:id:2642
    DOI: 10.37190/ord220101
    as

    Download full text from publisher

    File URL: https://ord.pwr.edu.pl/assets/papers_archive/2642%20-%20published.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.37190/ord220101?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
    ---><---

    References listed on IDEAS

    as
    1. Miin-Shen Yang & Zahid Hussain, 2018. "Fuzzy Entropy for Pythagorean Fuzzy Sets with Application to Multicriterion Decision Making," Complexity, Hindawi, vol. 2018, pages 1-14, November.
    2. K. Rahman & A. Ali & S. Abdullah & F. Amin, 2018. "Approaches to Multi-Attribute Group Decision Making Based on Induced Interval-Valued Pythagorean Fuzzy Einstein Aggregation Operator," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 343-361, November.
    3. Kifayat Ullah, 2021. "Picture Fuzzy Maclaurin Symmetric Mean Operators and Their Applications in Solving Multiattribute Decision-Making Problems," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-13, October.
    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. Shio Gai Quek & Ganeshsree Selvachandran & Florentin Smarandache & J. Vimala & Son Hoang Le & Quang-Thinh Bui & Vassilis C. Gerogiannis, 2020. "Entropy Measures for Plithogenic Sets and Applications in Multi-Attribute Decision Making," Mathematics, MDPI, vol. 8(6), pages 1-17, June.
    2. Zhang, Mengdan & Zhang, Chonghui & Shi, Qiule & Zeng, Shouzhen & Balezentis, Tomas, 2022. "Operationalizing the telemedicine platforms through the social network knowledge: An MCDM model based on the CIPFOHW operator," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    3. Zeeshan Ali & Tahir Mahmood & Miin-Shen Yang, 2020. "TOPSIS Method Based on Complex Spherical Fuzzy Sets with Bonferroni Mean Operators," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
    4. Areeba Naseem & Kifayat Ullah & Maria Akram & Darko Božanić & Goran Ćirović, 2022. "Assessment of Smart Grid Systems for Electricity Using Power Maclaurin Symmetric Mean Operators Based on T-Spherical Fuzzy Information," Energies, MDPI, vol. 15(21), pages 1-25, October.
    5. Tahir Mahmood & Ubaid ur Rehman & Zeeshan Ali & Muhammad Aslam & Ronnason Chinram, 2022. "Identification and Classification of Aggregation Operators Using Bipolar Complex Fuzzy Settings and Their Application in Decision Support Systems," Mathematics, MDPI, vol. 10(10), pages 1-19, May.
    6. Mujab Waqar & Kifayat Ullah & Dragan Pamucar & Goran Jovanov & Ðordje Vranješ, 2022. "An Approach for the Analysis of Energy Resource Selection Based on Attributes by Using Dombi T-Norm Based Aggregation Operators," Energies, MDPI, vol. 15(11), pages 1-23, May.
    7. Majed Albaity & Tahir Mahmood, 2022. "Medical Diagnosis and Pattern Recognition Based on Generalized Dice Similarity Measures for Managing Intuitionistic Hesitant Fuzzy Information," Mathematics, MDPI, vol. 10(15), pages 1-15, August.
    8. Mingwei Lin & Chao Huang & Zeshui Xu, 2019. "TOPSIS Method Based on Correlation Coefficient and Entropy Measure for Linguistic Pythagorean Fuzzy Sets and Its Application to Multiple Attribute Decision Making," Complexity, Hindawi, vol. 2019, pages 1-16, October.

    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:wut:journl:v:32:y:2022:i:1:p:5-24:id:2642. 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: Adam Kasperski (email available below). General contact details of provider: https://edirc.repec.org/data/iopwrpl.html .

    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.