Neutrosophic Matrix and Neutrosophic Fuzzy Matrix

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.