This paper presents a comparative analysis of the Gauss-Seidel and Successive Over-Relaxation (SOR) methods for solving large systems of linear equations. While direct methods like Gaussian elimination provide exact solutions, iterative methods are often preferred for large, sparse systems due to their computational efficiency. The SOR method, an enhanced version of the Gauss-Seidel method, introduces a relaxation parameter (?) to accelerate convergence. A computational program was developed to determine the optimal relaxation factor and minimize the number of iterations.
Gauss-Seidel method, SOR method, System of linear equations
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