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Another view on knowledge measures in atanassov intuitionistic fuzzy sets

  • Fuzzy systems and their mathematics
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Abstract

Information quantification in numerical form for any given data is very useful in decision-making problems. In Atanassov intuitionistic fuzzy sets (A-IFSs), such quantification becomes more important due to uncertainties such as intuitionism and fuzziness. Distribution of these uncertainties is a key to determine knowledge associated with Atanassov intuitionistic values (A-IFVs). In this paper, first distribution of the above-mentioned uncertainties and their relationship are discussed. Then, knowledge measures are defined as a function of entropy and uncertainty index, with certain desired properties. Existence of such knowledge measures has been established. Further, it is shown that how proposed knowledge measures are useful in multi-criteria group decision-making (MCGDM) problems.

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Authors and Affiliations

  1. Islamabad Model College for Boys, F-10/3, Islamabad, Pakistan

    Muhammad Irfan Ali

  2. Department of Mathematics, Hubei University for Nationalities, Enshi, 445000, Hubei Province, China

    Jianming Zhan

  3. KMUTT Fixed Point Research Laboratory, SCL 802 Fixed Point Laboratory, Department of Mathematics, Faculty of Science, King Mongkut’s University of Technology Thonburi (KMUTT), 126 Pracha Uthit Road, Bang Mod, Thrung Khru, Bangkok, 10140, Thailand

    Muhammad Jabir Khan

  4. Department of Mathematics and Statistics, International Islamic University Islamabad, Islamabad, Pakistan

    Tahir Mahmood & Haider Faizan

Authors
  1. Muhammad Irfan Ali
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  2. Jianming Zhan
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  3. Muhammad Jabir Khan
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  4. Tahir Mahmood
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  5. Haider Faizan
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Correspondence to Tahir Mahmood.

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Ali, M.I., Zhan, J., Khan, M.J. et al. Another view on knowledge measures in atanassov intuitionistic fuzzy sets. Soft Comput 26, 6507–6517 (2022). https://doi.org/10.1007/s00500-022-07127-3

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  • DOI: https://doi.org/10.1007/s00500-022-07127-3

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