A Comparative study of solution techniques for linear and nonlinear systems of differential equations

This study presents a comprehensive comparison of three advanced techniques for solving different systems of ordinary differential equations (ODEs), which include both linear and nonlinear systems. The proposed methods are the Multi-Step Differential Transform Method (MSDTM), the Adomian Decomposition Method (ADM), and the Residual Power Series Method (RPSM). These methods present the solutions without requiring discretization, linearization, or perturbation. Moreover, their solutions take the form of rapidly convergent series with easily computable components. The theoretical foundation, computational effectiveness, and suitability for various ODE systems are examined for each method. All algorithms are implemented entirely in MATLAB (version R2016b) using custom-built functions, without relying on built-in solvers or symbolic computation. The proposed methods were tested on a number of real-world problems, showing their superior performance over other existing methods. The paper discusses the strengths and limitations of each method, focusing on their performance in terms of convergence, stability, and ease of implementation. The findings provide useful insights for researchers and practitioners in selecting approximate solution techniques for certain ODE systems, hence contributing to the improvement of numerical and semi-analytical methods in applied mathematics.

Authors

Institutions

Publication Details

Journal
Alfarama Journal of Basic & Applied Sciences
Published
2025-11-24
DOI
https://doi.org/10.21608/ajbas.2025.409005.1273
Primary Topic
Numerical methods for differential equations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Comparative study of solution techniques for linear and nonlinear systems of differential equations

Yasser Mohamed Hamada, Dalia Awad, Mennat-Allah Mohamed Fawzy, Ebrahim Rafat Ebrahim
Alfarama Journal of Basic & Applied Sciences
Numerical methods for differential equations
article

A Comparative study of solution techniques for linear and nonlinear systems of differential equations

Yasser Mohamed Hamada, Dalia Awad, Mennat-Allah Mohamed Fawzy, Ebrahim Rafat Ebrahim
article en

Abstract

This study presents a comprehensive comparison of three advanced techniques for solving different systems of ordinary differential equations (ODEs), which include both linear and nonlinear systems. The proposed methods are the Multi-Step Differential Transform Method (MSDTM), the Adomian Decomposition Method (ADM), and the Residual Power Series Method (RPSM). These methods present the solutions without requiring discretization, linearization, or perturbation. Moreover, their solutions take the form of rapidly convergent series with easily computable components. The theoretical foundation, computational effectiveness, and suitability for various ODE systems are examined for each method. All algorithms are implemented entirely in MATLAB (version R2016b) using custom-built functions, without relying on built-in solvers or symbolic computation. The proposed methods were tested on a number of real-world problems, showing their superior performance over other existing methods. The paper discusses the strengths and limitations of each method, focusing on their performance in terms of convergence, stability, and ease of implementation. The findings provide useful insights for researchers and practitioners in selecting approximate solution techniques for certain ODE systems, hence contributing to the improvement of numerical and semi-analytical methods in applied mathematics.

Alfarama Journal of Basic & Applied SciencesVol. 0(0)
Suez Canal University (EG), Port Said University (EG)
Openalex Percentile: Top 49%
Numerical methods for differential equations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.