Systematic review of decision making algorithms in extended neutrosophic sets

Khan, Mohsin and Son, Le Hoang and Ali, Mumtaz and Chau, Hoang Thi Minh and Na, Nguyen Thi Nhu and Smarandache, Florentin (2018) Systematic review of decision making algorithms in extended neutrosophic sets. Symmetry, 10 (8):314. pp. 1-28.

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Abstract

The Neutrosophic set (NS) has grasped concentration by its ability for handling indeterminate, uncertain, incomplete, and inconsistent information encountered in daily life. Recently, there have been various extensions of the NS, such as single valued neutrosophic sets (SVNSs), Interval neutrosophic sets (INSs), bipolar neutrosophic sets (BNSs), Refined Neutrosophic Sets (RNSs), and triangular fuzzy number neutrosophic set (TFNNs). This paper contains an extended overview of the concept of NS as well as several instances and extensions of this model that have been introduced in the last decade, and have had a significant impact in literature. Theoretical and mathematical properties of NS and their counterparts are discussed in this paper as well. Neutrosophic-set-driven decision making algorithms are also overviewed in detail.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences (1 Jul 2013 - 5 Sep 2019)
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences (1 Jul 2013 - 5 Sep 2019)
Date Deposited: 11 Feb 2019 00:25
Last Modified: 01 Jun 2021 00:10
Uncontrolled Keywords: multi attribute algorithms; decision making; neutrosophic set; literature review
Fields of Research (2008): 01 Mathematical Sciences > 0102 Applied Mathematics > 010201 Approximation Theory and Asymptotic Methods
Fields of Research (2020): 49 MATHEMATICAL SCIENCES > 4901 Applied mathematics > 490101 Approximation theory and asymptotic methods
Identification Number or DOI: https://doi.org/10.3390/sym10080314
URI: http://eprints.usq.edu.au/id/eprint/35454

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