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

M Kavitha; Sive M; P  Murugadas; K Rameshware

Authors

M Kavitha Department of Mathematics, Chennai Institute of Technology, Chennai, India 1;
Sive M Department of Mathematics, St. Joseph’s Institute of Technology, Chennai, India;
P Murugadas Department of Mathematics, Annamalai University, Annamalai Nagar, India;
K Rameshware Department of Mathematics, Bharath Institute of Higher Education and Research, Chennai;

Keywords:

Fuzzy Neutrosophic Soft Matrix (FNSM), Nilpotent Fuzzy Neutrosophic Soft Matrix (NFNSM), Transitive Fuzzy Neutrosophic Soft Matrix (T FNSM), Controllable Fuzzy Neutrosophic Soft Matrix CFNSM, Python

Abstract

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.

DOI: 10.5281/zenodo.17114543