Numerical Solution of A Class of Fourth-Order Differential Equations with Initial Conditions
Authors
Nsien, Edwin Frank
Department of Statistics, University of Uyo, Uyo, Akwa Ibom State, Nigeria (NG)
Abasiekwere, Ubon Akpan
Department of Mathematics, University of Uyo, Uyo, Akwa Ibom State, Nigeria (NG)
Article Information
DOI: 10.51583/IJLTEMAS.2025.140500012
Subject Category: Computational methods in Ordinary Differential Equations
Volume/Issue: 14/5 | Page No: 73-87
Publication Timeline
Submitted: 2025-05-31
Published: 2025-05-31
Abstract
Abstract: This paper presents the Runge-Kutta (RK4) method of order four for solving initial value problems of fourth-order ordinary differential equations. The proposed method is derived and is observed to be efficient and practically well-suited for handling high-order initial value problems. Two modal examples (linear and non-linear) are presented to demonstrate the reliability, accuracy and easy implementability of the method. The results obtained show a high level of accuracy when compared with the analytical solution.
Keywords
Runge-Kutta, ordinary differential equations, initial value problem, finite difference method, numerical approximation
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References
1. Ahmadianfar, I., Heidari, A. A., Gandomi, A. H., Chu, X., Chen, H. (2021). RUN beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method, Expert Systems with Applications, Vol. 181 [Google Scholar] [Crossref]
2. Iyenga, S.R. & Jain, R. K, (2009). Numerical methods. New Delhi: New Age International (p) Limited Publishers. [Google Scholar] [Crossref]
3. Sakar, S. (2006). Quantum phase diagram of a super conducting quantum dots array. EPL (Europhysics letters). [Google Scholar] [Crossref]
4. Burden, R.L. & Douglass, J.F. (2011). Numerical analysis. New York: Richard Straton. [Google Scholar] [Crossref]
5. Davis, M. (2010). Finite difference methods. London: Department of Mathematics, Imperial College. [Google Scholar] [Crossref]
6. Evans, L.C. (1997). Partial differential equations. Berkeley: American Mathematical Society. [Google Scholar] [Crossref]
7. Gonze, D. (2012). Linear difference equations. Master en Bioinformatique et modelisation. [Google Scholar] [Crossref]
8. Zhang, D. K. (2019). Discovering New Runge–Kutta Methods Using Unstructured Numerical Search, Vanderbilt University, Thesis, DOI: 10.48550/arXiv.1911.00318 [Google Scholar] [Crossref]
9. Ghoreishi, F., Ghaffari, R. and Saad, N. (2023). Fractional Order Runge–Kutta Methods, Fractal and Fractional, 7(3), 245; doi.org/10.3390/fractalfract7030245 [Google Scholar] [Crossref]
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