A state-of-the-art survey on spherical fuzzy sets


ÖZCEYLAN E., ÖZKAN B., KABAK M., DAĞDEVİREN M.

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, vol.42, no.1, pp.195-212, 2022 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 42 Issue: 1
  • Publication Date: 2022
  • Doi Number: 10.3233/jifs-219186
  • Journal Name: JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
  • Journal Indexes: Science Citation Index Expanded, Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Page Numbers: pp.195-212
  • Keywords: Spherical fuzzy sets, fuzzy logic, literature review, AGGREGATION OPERATORS, EXTENSION, SELECTION, OPERATIONS

Abstract

In addition to the well-known fuzzy sets, a novel type of fuzzy set called spherical fuzzy set (SFS) is recently introduced in the literature. SFS is the generalized structure over existing structures of fuzzy sets (intuitionistic fuzzy sets-IFS, Pythagorean fuzzy sets-PFS, and neutrosophic fuzzy sets-NFS) based on three dimensions (truth, falsehood, and indeterminacy) to provide a wider choice for decision-makers (DMs). Although the SFS has been introduced recently, the topic attracts the attention of academicians at a remarkable rate. This study is the expanded version of the authors' earlier study by Ozceylan et al. [1]. A comprehensive literature review of recent and state-of-the-art papers is studied to draw a framework of the past and to shed light on future directions. Therefore, a systematic review methodology that contains bibliometric and descriptive analysis is followed in this study. 104 scientific papers including SFS in their titles, abstracts and keywords are reviewed. The papers are then analyzed and categorized based on titles, abstracts, and keywords to construct a useful foundation of past research. Finally, trends and gaps in the literature are identified to clarify and to suggest future research opportunities in the fuzzy logic area.