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Modeling Human Vagueness and Imprecision: From Fuzzy Sets to Hesitant Fuzzy Sets

Author

Listed:
  • B. Farhadinia

    (Department of Mathematics, Quchan University of Technology, Quchan, Iran)

  • F. Chiclana

    (��Institute of Artificial Intelligence (IAI), Faculty of Computing, Engineering and Media, De Montfort University, Leicester, UK)

Abstract

Hesitant fuzzy set has been able to receive an immense concern on the basis of several studies in both theoretical and practical viewpoints that have reported its adverse effects. During the last 12 years, there has been a growing interest in different extensions of hesitant fuzzy set theory which can generates and adopts to improve hesitant fuzzy capacity to address the increase in information complexity. Through this contribution, we intend to conduct a comprehensive literature review on “Hesitant Fuzzy†extensions those have been rarely reported previously. In view of this matter, this paper takes the literature on “Hesitant Fuzzy†extensions in the core collection database of Web of Science as the research object, and moreover, it uses the bibliometric software package of VOSviewer to visually analyze the themes of “Hesitant Fuzzy†researches from different aspects such as general statistics, top authors, the affiliation of top authors, the country of top authors, the document types and the subject areas. Furthermore, this contribution analyses the chronological development of “Hesitant Fuzzy†extensions which have been more frequently and thoroughly reviewed, including the general-based, the linguistic term-based, the q-rung orthopair-based and the probabilistic-based extensions of hesitant fuzzy sets. Last, a number of directions for future research are put forward.

Suggested Citation

  • B. Farhadinia & F. Chiclana, 2023. "Modeling Human Vagueness and Imprecision: From Fuzzy Sets to Hesitant Fuzzy Sets," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 715-736, November.
  • Handle: RePEc:wsi:nmncxx:v:19:y:2023:i:03:n:s179300572350031x
    DOI: 10.1142/S179300572350031X
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