Numerical Approaches for Solving Mixed Volterra-Fredholm Fractional Integro-Differential Equations
Authors
N. M. A. Nik Long1, 2, *, K. Alsa’di1
1Department of Mathematics, Faculty of Science, Universiti Putra Malaysia, UPM, 43400, Serdang, Selangor, Malaysia
2Institute for Mathematical Research, Universiti Putra Malaysia, UPM, 43400, Serdang, Selangor, Malaysia
*Corresponding author.
Email: nmasri@upm.edu.my
Corresponding Author
N. M. A. Nik Long
Available Online 12 December 2022.
- DOI
- 10.2991/978-94-6463-014-5_26How to use a DOI?
- Keywords
- Fractional integro-differential equation; Caputo derivatives; Adomian polynomial; Residual function
- Abstract
In this paper, an approximate solution for solving nonlinear mixed Volterra-Fredholm fractional integro-differential equations is presented. The fractional derivative is defined in terms of Caputo type. Two methods are suggested: Adomin Decomposition Method (ADM) and Residual Power Series Method (RPSM). In these methods, Adomian polynomials and residual function are derived. The fractional Volterra-Fredholm integro-differential equation is reduced to a recurrence formula, in which it can be solved rather straightforward. Numerical examples demonstrate the efficiency and accuracy of ADM over RPSM.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - N. M. A. Nik Long AU - K. Alsa’di PY - 2022 DA - 2022/12/12 TI - Numerical Approaches for Solving Mixed Volterra-Fredholm Fractional Integro-Differential Equations BT - Proceedings of the International Conference on Mathematical Sciences and Statistics 2022 (ICMSS 2022) PB - Atlantis Press SP - 278 EP - 285 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-014-5_26 DO - 10.2991/978-94-6463-014-5_26 ID - Long2022 ER -