Neutrosophic Matrix and Neutrosophic Fuzzy Matrix
Madhumangal Pal
Additional contact information
Madhumangal Pal: Vidyasagar University, Department of Applied Mathematics
Chapter Chapter 10 in Recent Developments of Fuzzy Matrix Theory and Applications, 2024, pp 381-423 from Springer
Abstract:
Abstract After the development of the fuzzy set (FS) theory, many problems with non-random uncertainty are tackled using this theory. While solving these problems, the researchers observed that there are many cases where FS is not sufficient to find the answer. In 1983 [10], Atanassov introduced an intuitionistic fuzzy set (IFS), a very good extension of FS. A beautiful insight of IFS is that it incorporates two parameters known as membership value and non-membership value. There is a restriction on these values, their sum is less than or equal to 1. If the sum is exactly equal to 1 for all members, then there is nothing new in IFS; in this case, IFS becomes FS. Basically, IFS deals with the problems when FS fails to solve them or the available information is not sufficient to explain/solve the problem completely.
Date: 2024
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-56936-4_10
Ordering information: This item can be ordered from
http://www.springer.com/9783031569364
DOI: 10.1007/978-3-031-56936-4_10
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().