The Solution of Non-Linear Equations System Containing Interpolation Functions by Relaxing the Newton Method

Authors

  • Nur Rokhman Universitas Gadjah Mada
  • Erwin Eko Wahyudi Universitas Gadjah Mada
  • Janoe Hendarto Universitas Gadjah Mada

DOI:

https://doi.org/10.21512/comtech.v13i1.7322

Keywords:

non-linear equation, interpolation function, Newton method

Abstract

Many world phenomena lead to nonlinear equations systems. For some applications, the non-linear equations which construct the non-linear equations system are interpolation functions. However, the interpolation functions are usually not represented as mathematical expressions but as computer programs in specific programming languages. The research proposed using the relaxed Newton method to solve the non-linear equations system that contained interpolation functions. The interpolation functions were represented in the R programming language. Then, the experiment used the Spline interpolation function to construct a two-dimensional non-linear equations system. Eleven initial guesses, maximum of ten-time iterations, and 10-7 precision were applied. The solution of the non-linear equations system and the iteration needed on each initial guess were observed. The experiment shows that the proposed method works well for solving the non-linear equations system constructed by Spline interpolation functions. By observing the initial guesses used in the experiment, there are four possible results: true solution, spurious solution, false solution, and no solution. Applying 11 initial guesses have five initial guesses resulting in true solutions, one initial guess in spurious solution, three initial guesses in false solutions, and one initial guess in no solution. The discussions imply that this method can be generalized to the three-dimensional non-linear equations system or higher dimensions.

Dimensions

Plum Analytics

Author Biographies

Nur Rokhman, Universitas Gadjah Mada

Department of Computer Sciences and Electronics, Faculty of Mathematics and Natural Sciences

Erwin Eko Wahyudi, Universitas Gadjah Mada

Department of Computer Sciences and Electronics, Faculty of Mathematics and Natural Sciences

Janoe Hendarto, Universitas Gadjah Mada

Department of Computer Sciences and Electronics, Faculty of Mathematics and Natural Sciences

References

Abubakar, A. B., & Waziri, M. Y. (2016). A matrix-free approach for solving systems of nonlinear equations. Journal of Modern Methods in Numerical Mathematics, 7(1), 1‒9.

Ahmad, F., Serra-Capizzano, S., Ullah, M. Z., & Al-Fhaid, A. S. (2016). A family of iterative methods for solving systems of nonlinear equations having unknown multiplicity. Algorithms, 9(1), 1‒10. https://doi.org/10.3390/a9010005

Ahmadi, M., Esmaeili, H., & Erfanifar, R. (2016). Solving system of nonlinear equations by using a new three-step method. Control and Optimization in Applied Mathematics, 1(2), 53–62.

Atkinson, K., & Han, W. (2004). Elementary numerical analysis. Wiley.

Dontchev, A. L., Qi, H. D., Qi, L., & Yin, H. (2002). A Newton method for shape-preserving spline interpolation. SIAM Journal on Optimization, 13(2), 588–602. https://doi.org/10.1137/S1052623401393128

Dwail, H. H., & Shiker, M. A. K. (2021). Using Trust Region method with BFGS technique for solving nonlinear systems of equations. Journal of Physics: Conference Series, 1818, 1‒9. https://doi.org/10.1088/1742-6596/1818/1/012022

Ghorbanzadeh, M., & Soleymani, F. (2015). A quartically convergent Jarratt-type method for nonlinear system of equations. Algorithms, 8(3), 415–423. https://doi.org/10.3390/a8030415

Grosan, C., & Abraham, A. (2008). A new approach for solving nonlinear equations systems. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 38(3), 698–714. https://doi.org/10.1109/TSMCA.2008.918599

Hashim, K. H., Dreeb, N. K., Dwail, H. H., Mahdi, M. M., Wasi, H. A., Shiker, M. A. K., & Hussein, H. A. (2019). A new line search method to solve the nonlinear systems of monotone equations. Journal of Engineering and Applied Sciences, 14, 10080–10086. https://doi.org/10.36478/jeasci.2019.10080.10086

Halilu, A. S., & Waziri, M. Y. (2020). Solving systems of nonlinear equations using improved double direction method. Journal of the Nigerian Mathematical Society, 39(2), 287–301.

Hosseini, M. M., & Kafash, B. (2010). An efficient algorithm for solving system of nonlinear equations. Applied Mathematical Sciences, 4(3), 119–131.

Isaac, A., Stephen, T. B., & Seidu, B. (2021). A new Trapezoidal-Simpson 3/8 method for solving systems of nonlinear equations. American Journal of Mathematical and Computer Modelling, 6(1), 1–8. https://doi.org/10.11648/j.ajmcm.20210601.11

Khirallah, M. Q., & Hafiz, M. A. (2013). Solving system of nonlinear equations using family of Jarratt methods. International Journal of Differential Equations and Applications, 12(2), 69–83. https://doi.org/10.12732/ijdea.v12i2.931

Liu, Z., & Fang, Q. (2015). A new Newton-type method with third-order for solving systems of nonlinear equations. Journal of Applied Mathematics and Physics, 3(10), 1256–1261. https://doi.org/10.4236/jamp.2015.310154

Madhu, K., & Jayaraman, J. (2017). Some higher order Newton-like methods for solving system of nonlinear equations and its applications. International Journal of Applied and Computational Mathematics, 3, 2213–2230. https://doi.org/10.1007/s40819-016-0234-z

Mahwash, K. N., & Gyang, G. D. (2018). Numerical solution of nonlinear systems of algebraic equations. International Journal of Data Science and Analysis, 4(1), 20‒23. https://doi.org/10.11648/j.ijdsa.20180401.14

Mohammad, H., & Waziri, M. Y. (2015). On Broyden-like update via some quadratures for solving nonlinear systems of equations. Turkish Journal of Mathematics, 39, 335–345. https://doi.org/10.3906/mat-1404-41

Montazeri, H., Soleymani, F., Shateyi, S., & Motsa, S. S. (2012). On a new method for computing the numerical solution of systems of nonlinear equations. Journal of Applied Mathematics, 2012, 1‒15. https://doi.org/10.1155/2012/751975

Osinuga, I. A., & Yusuff, S. O. (2018). Quadrature based Broyden-like method for systems of nonlinear equations. Statistics, Optimization & Information Computing, 6(1), 130–138. https://doi.org/10.19139/soic.v6i1.471

Rokhman, N. (2011). Secton: A combination of Newton Method and Secant method for solving non linear equations. In Seminar Nasional Aplikasi Teknologi Informasi (SNATI) (pp. 50–52).

Rokhman, N. (2013). The implementation of Secton method for solving systems of non linear equations. In International Conference on Engineering and Technology Development (ICETD) (pp. 80–84).

Rokhman, N. (2017). Solving non-linear equations containing spline interpolation function by relaxing the Newton method. In 2017 Second International Conference on Informatics and Computing (ICIC) (pp. 1–5). IEEE. https://doi.org/10.1109/IAC.2017.8280641

Ruiz-Oltra, J. M., Gómez-Quiles, C., & Gómez-Expósito, A. (2016). Offset-assisted factored solution of nonlinear systems. Algorithms, 9(1), 1–14. https://doi.org/10.3390/a9010002

Shacham, M., & Brauner, N. (2017). Solving a system of nonlinear algebraic equations: You only get error messages-What to do next? Chemical Engineering Education, 51(2), 75–82.

Taheri, S., & Mammadov, M. (2012). Solving systems of nonlinear equations using a globally convergent optimization algorithm. Global Journal of Technology & Optimization, 3, 132–138.

Wang, X., & Fan, X. (2016). Two efficient derivative-free iterative methods for solving nonlinear systems. Algorithms, 9(1), 1–10. https://doi.org/10.3390/a9010014

Downloads

Published

2022-02-03

Issue

Section

Articles
Abstract 778  .
PDF downloaded 525  .