Fitted Reproducing Kernel Method for Solving a Class of Third-Order Periodic Boundary Value Problems
- 1 Department of Applied Science, Ajloun College, Al Balqa Applied University, Ajloun 26816, Jordan
- 2 Department of Mathematics, Faculty of Science, Zarqa University, Zarqa 13110, Jordan
- 3 Department of Mathematics, University of Malakand, Chakadara Dir(L), Khyber Pakhtunkhwa, Pakistan
- 4 Department of Applied Science, Faculty of Engineering Technology, Al-Balqa Applied University, Amman 11942, Jordan
In this article, the reproducing kernel Hilbert space W24 [0, 1] is employed for solving a class of third-order periodic boundary value problem by using fitted reproducing kernel algorithm. The reproducing kernel function is built to get fast accurately and efficiently series solutions with easily computable coefficients throughout evolution the algorithm under constraint periodic conditions within required grid points. The analytic solution is formulated in a finite series form whilst the truncated series solution is given to converge uniformly to analytic solution. The reproducing kernel procedure is based upon generating orthonormal basis system over a compact dense interval in sobolev space to construct a suitable analytical-numerical solution. Furthermore, experiments results of some numerical examples are presented to illustrate the good performance of the presented algorithm. The results indicate that the reproducing kernel procedure is powerful tool for solving other problems of ordinary and partial differential equations arising in physics, computer and engineering fields.
Copyright: © 2016 Asad Freihat, Radwan Abu-Gdairi, Hammad Khalil, Eman Abuteen, Mohammed Al-Smadi and Rahmat Ali Khan. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- 1,992 Views
- 1,435 Downloads
- 6 Citations
- Boundary Value Problem
- Error Estimation and Error Bound
- Reproducing Kernel Theory