MATRIX METHODS IN COMPUTATIONAL MODELING AND MULTIDISCIPLINARY SYSTEMS ANALYSIS

Abstract

Matrices constitute a fundamental mathematical structure widely applied in engineering, physics, computer science, and economics. They provide a compact representation of linear systems, transformations, and multidimensional data. From solving systems of linear equations to powering machine learning algorithms, matrix methods enable efficient computation and structural modeling. This article investigates the theoretical basis and applied significance of matrix analysis in modern scientific and technological research.