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Neutrosophic Matrix and Neutrosophic Fuzzy Matrix

In: Recent Developments of Fuzzy Matrix Theory and Applications

Author

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  • Madhumangal Pal

    (Vidyasagar University, Department of Applied Mathematics)

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.

Suggested Citation

  • Madhumangal Pal, 2024. "Neutrosophic Matrix and Neutrosophic Fuzzy Matrix," Springer Books, in: Recent Developments of Fuzzy Matrix Theory and Applications, chapter 0, pages 381-423, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-56936-4_10
    DOI: 10.1007/978-3-031-56936-4_10
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