UPSI Digital Repository (UDRep)
Start | FAQ | About
Menu Icon

QR Code Link :

Type :thesis
Subject :QA Mathematics
Main Author :Aboamemah, Ahmed Hadi Mohammed
Title :Numerical study on some iterative methods for solving nonlinear equations by using Scilab programming
Place of Production :Tanjong Malim
Publisher :Fakulti Sains dan Matematik
Year of Publication :2019
Corporate Name :Universiti Pendidikan Sultan Idris
PDF Guest :Click to view PDF file

Abstract : Universiti Pendidikan Sultan Idris
This research aimed to investigate the most efficient iterative method in solving scalar nonlinear equations. There are three iterative methods that are used to solve the nonlinear scalar equations that are Bisection, Secant and Newton Raphson’s methods. These three iterative methods have different order of convergence. Bisection method is linearly convergence while Secant method is super linear and Newton-Raphson method has quadratic convergence. It is well known that the method that has a higher order of convergence, will perform much faster than others. Seven nonlinear scalar equations are considered based on the combinations of two or three functions and are solved by the Bisection, Secant and Newton-Raphson methods using Scilab programming language. The tolerance used is 10−10 and the performances of these methods are based on number of function evaluation, number of iterations, and computational or CPU time. Based on the numerical results of the seven nonlinear equations, it is observed that Newton-Raphson method is still the most efficient method but not for all the equations. Bisection method has fixed performances on all the nonlinear equations however, the method failed to converge for the imaginary root. On the other hand, the performance of Secant method is almost similar to Newton-Raphson method except for the nonlinear Equations (4.4), and (4.5) on the interval [1.3,2] and [0,1] respectively. In conclusion, Newton-Raphson method remains the best but not for all nonlinear equations since there are realistic circumstances that makes Newton-Raphson converges either slower or identical to Secant method. It is also proven that Secant method can perform faster than Newton-Raphson method depending on the form of the curve functions that corresponds to the approximate values. As implications, more than three combinations of the functions can be investigated and also the research can be extended to system of nonlinear equations.

References

Adhikari, I. (2017). Interval and speed of convergence on iterative methods. Himalayan

Physics, 6:112–114.

 

Akram, S. and Ul Ann, Q. (2015).  Newton raphson method.  International Journal of Scienti?c & 

Engineering Research, 6(7):1748–1752.

 

Al-Baali, M., Spedicato, E., and Maggioni, F. (2014). Broyden’s quasi-newton methods for a 

nonlinear system of equations and unconstrained optimization:  a review and open problems. 

Optimization Methods and Software, 29(5):937–954.

 

Burden, R. L., Faires, J. D., and Burden, A. (2014).  Numerical analysis.  Brooks/Cole, USA.

 

Candela, V. and Peris, R. (2015). The rate of multiplicity of the roots of nonlinear equa- tions 

and its application to iterative methods. Applied Mathematics and Computation, 264:417–430.

 

Chhabra, C. (2014). Improvements in the bisection method of ?nding roots of an equa- tion. Advance 

Computing Conference (IACC), 2014 IEEE International, 2014:11–16.

 

Díez, P. (2003). A note on the convergence of the secant method for simple and multiple roots. 

Applied Mathematics Letters, 16(8):1211–1215.

 

Ehiwario, J. C. and Aghamie, S. O. (2014).  Comparative study of bisection, newton- raphson and 

secant methods of root-?nding problems.  IOSR Journal of Engineering (IOSRJEN), 4(04):2278–8719.

 

Hasan,  A. (2016).   Numerical study of some iterative methods for solving nonlinear equations. 

International Journal of Engineering Science Invention, 5(2):01–10.

 

Hasan, A. and Ahmad, N. (2015).  Comparative study of a new iterative method with that of newton’s 

method for solving algebraic and transcendental equations. 4(3):32– 37.

 

Henrici, P. (1964). Elements of Numerical Analysis. Wiley, Switzerland.

 

Intep, S. (2018).  A review of bracketing methods for ?nding zeros of nonlinear func-

tions. Applied Mathematical Sciences, 12(3):137–146.

 

Jain,  M. K. (2003).   Numerical methods for scienti?c and engineering computation.

New Age International.

 

Kumar, R. and Vipan (2015). Comparative analysis of convergence of various numerical methods. 

Journal of Computer and Mathematical Sciences, 6(6):290–297.

 

McClarren, R. G. (2018a). Chapter 12 - Closed Root Finding Methods, pages 215–228.

Academic Press, USA.

 

McClarren, R. G. (2018b).  Chapter 13 - Open Root Finding Methods, pages 229–249.

Academic Press, USA.

 

Nijmeijer, M. J. P. (2014).  A method to accelerate the convergence of the secant algo- rithm. 

Advances in Numerical Analysis, 2014:1–14.

 

Papakonstantinou, J. M. and Tapia, R. A. (2013).  Origin and evolution of the secant method in one 

dimension. The American Mathematical Monthly, 120(6):500–517.

 

Polyak, B. T. (2007).  Newtons method and its use in optimization.  European Journal of Operational 

Research, 181(3):1086–1096.

 

Ramos, H. and Vigo-Aguiar, J. (2015).  The application of newtons method in vector form for solving 

nonlinear scalar equations where the classical newton method fails. Journal of Computational and 

Applied Mathematics, 275:228–237.

 

Salleh, Z., Yusop, M. Y. M., and Ismail, S. B. (2012).   Basic of numerical computa- tional using 

scilab programming.  Proceedings of the 2nd International Conference on Mathematical Applications 

in Engineering (ICMAE2012), 2012:1–8.

 

Shanker, G. R. (2006). Numerical analysis. New Age International, New Delhi. 

 

Solanki, C., Thapliyal, P., and Tomar, K. (2014).  Role of bisection method.  Interna-

tional Journal of Computer Applications Technology and Research, 3(9):533–535.

 

Srivastava, R. B. and Srivastava, S. (2011). Numerical rate of convergence of bisection method. 

Journal of Chemical, Biological and Physical Sciences (JCBPS), 2(1):451– 461.

 

Vianello, M.and Zanovello, R. (1992).  On the superlinear convergence of the secant

method. The American mathematical monthly, 99(8):758–761.

 

Walter, E. (2014). Numerical methods and optimization. Springer, United States. Zarowski, C. J. 

(2004).  An introduction to numerical analysis for electrical and com-

puter engineers. John Wiley & Sons, New York.

 

 

 


This material may be protected under Copyright Act which governs the making of photocopies or reproductions of copyrighted materials.
You may use the digitized material for private study, scholarship, or research.

Back to previous page

Installed and configured by Bahagian Automasi, Perpustakaan Tuanku Bainun, Universiti Pendidikan Sultan Idris
If you have enquiries, kindly contact us at pustakasys@upsi.edu.my or 016-3630263. Office hours only.