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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Majalah Ilmiah Matematika dan Statistika (MIMS)
M Ziaul Arif, M Ziaul
Department of Mathematics, Faculty of Sciences, University of Jember
Mathematics

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Modified Chebyshev Collocation Method for Solving Differential Equations Arif, M Ziaul; Kamsyakawuni, Ahmad; Halikin, Ikhsanul
CAUCHY Vol 3, No 4 (2015): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (787.664 KB) | DOI: 10.18860/ca.v3i4.2923

Abstract

This paper presents derivation of alternative numerical scheme for solving differential equations, which is modified Chebyshev (Vieta-Lucas Polynomial) collocation differentiation matrices. The Scheme of modified Chebyshev (Vieta-Lucas Polynomial) collocation method is applied to both Ordinary Differential Equations (ODEs) and Partial Differential Equations (PDEs) cases. Finally, the performance of the proposed method is compared with finite difference method and the exact solution of the example. It is shown that modified Chebyshev collocation method more effective and accurate than FDM for some example given.
PERBANDINGAN ALGORITMA PARTICLE SWARM OPTIMIZATION (PSO) DAN ALGORITMA GLOWWORM SWARM OPTIMIZATION (GSO) DALAM PENYELESAIAN SISTEM PERSAMAAN NON LINIER Azmi, Ana Ulul; Hidayat, Rusli; Arif, M Ziaul
Majalah Ilmiah Matematika dan Statistika Vol 19 No 1 (2019): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v19i1.17263

Abstract

Non-linear equation system is one of the mathematics problems which difficult to solve. Several methods have been introduced to solve the problems. Newton-Raphson method is the most common and widely used as the basis for evolving the latest numerical methods. However, this method requires the derivative of each equation with respect to every variable when calculating the Jacobian. Naturally, obtaining the derivative is challenging in certain cases. In addition, it needs a proper initial value to obtain the converged solution. Therefore, the new technique with a simple random initial value is urgently needed. In this study, it is shown the implementation of the two metaheuristic optimization methods, including Particle Swarm Optimization (PSO) and the Glowworm Swarm Optimization (GSO) to estimate the solution of a non-linear equation system. Several examples of nonlinear equation system were used for evaluating and testing the performance and the accuracy of both algorithms. In this simulation, the results show that PSO converged to the exact solution (global optimum) better than Glowworm Swarm Optimization (GSO). Keywords: Non-Linear Equation Systems, Particle Swarm Optimization (PSO), Glowworm Swarm Optimization (GSO)
Co-Authors Ahmad Kamsyakawuni Azmi, Ana Ulul Ikhsanul Halikin, Ikhsanul Rusli Hidayat