The aim of this article is to study the concept of unique solvability of max-min fuzzy neutrosophic soft matrix equation and strong regularity of fuzzy neutrosophic soft matrices over Fuzzy Neutrosophic Soft Algebra (FNSA). A Fuzzy Neutrosophic Soft Matrix (FNSM) is said to have Strong, Linear Independent (SLI) column (or, in the case of fuzzy neutrosophic soft square matrices, to be strongly regular) if for some fuzzy neutrosophic soft vector b the system A⊗x = b has a unique solution. A necessary and sufficient condition for linear system of equation over a FNSA to have a unique solution is formulated and the equivalent condition for FNSM to have SLI column and Strong Regular (SR) are presented. Moreover trapezoidal algorithm for testing these properties is reviewed. Manuscript profile

In this paper, ‎The powers of fuzzy neutrosophic soft square matrices (FNSSMs) under the operations $\oplus(=max)$ and $\otimes(=min)$ are studied‎. ‎We show that the powers of a given FNSM stabilize if and only if its orbits stabilize for each starting fuzzy neutrosophic soft vector (FNSV) and prove a necessary and sufficient condition for this property using the associated graphs of the FNSM‎. ‎Applications of the obtained results to several spacial classes of FNSMs (including circulants) are given‎. Manuscript profile