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Jurnal Pendidikan Matematika
Published by Indonesian Journal Publisher
ISSN : -     EISSN : 30309263     DOI : https://doi.org/10.47134/ppm
Core Subject : Education,
Education Mathematics Other
Jurnal Pendidikan Matematika ISSN 3030-9263 is a scientific journal published by Indonesian Journal Publisher. This journal publishes four issues annually in the months of November, February, May, and August. This journal only accepts original scientific research works (not a review) that have not been published by other media. The focus and scope of Jurnal Pendidikan Matematika include mathematics learning strategies, mathematics learning design, development of mathematics learning tools, analysis in the field of mathematics education, and various things related to mathematics learning from elementary school to college level.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 11 Documents
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Search results for , issue "Vol. 2 No. 4 (2025): August" : 11 Documents clear
Preconditioning Techniques in Krylov Subspace Methods Najm, Zina Jabbar
Jurnal Pendidikan Matematika Vol. 2 No. 4 (2025): August
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ppm.v2i4.2054

Abstract

This study discusses preconditioning approaches to address large, sparse linear systems as well as Krylov subspace methods. Among others, computational fluid dynamics, structural analysis, and electromagnetic simulations use Krylov methods like the Conjugate Gradient (CG) and Generalized Minimal Residual (GMRES). These techniques use iterative approximations that approach to the solution by projecting the problem onto a Krylov subspace. The efficiency of Krylov methods is greatly influenced by the selection of preconditions, which help the system's conditioning and so accelerate convergence. Jacobi Preconditioning, Incomplete LU Decomposition (ILU), and Multigrid Preconditioning are examples of preconditioning techniques. Though it has advantages, preconditioning has disadvantages including choosing the proper conditions and controlling memory and costing calculations. Further investigated were possible changes including adaptive and nonlinear preconditioning as well as the integration of Artificial Intelligence

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