Treffer: COMPUTATIONAL STUDY OF FUZZY NEUTROSOPHIC SOFT MATRICES IN PYTHON: CONSISTENCY AND WEAK TRANSITIVITY.

In this study, we introduce a novel framework for defining and analyzing two specific types of Fuzzy Neutrosophic Soft Matrices (FNSMs): consistent and weakly transitive. These matrix classes are modelled and assessed using Python-based computational techniques. We establish that both types exhibit controllability and present a Python-compatible formulation for deriving the canonical form of a Weakly Transitive FNSM (WT-FNSM). Fundamental algebraic and structural properties such as nilpotency, symmetry, transitivity, and weak transitivity are investigated through programmatic simulations. Additionally, we explore the connection between consistent and weakly transitive FNSMs and finite fuzzy neutrosophic relations, emphasizing their applicability in various practical and academic domains. The controllability of WT-FNSMs is further validated through algorithmic evaluation. To support the theoretical results, appropriate Python-based examples and simulations are provided. A key contribution of this work is a versatile Python tool designed for FNSMs, which is also adaptable for use with fuzzy matrices, intuitionistic fuzzy matrices, and fuzzy neutrosophic matrices. [ABSTRACT FROM AUTHOR]