IOSR Journal of Engineering (IOSRJEN) Comparative Study of Bisection, Newton-Raphson and Secant Methods of Root-Finding Problems (original) (raw)

The study is aimed at comparing the rate of performance, viz-aviz, the rate of convergence of Bisection method, Newton-Raphson method and the Secant method of root-finding. The software, mathematica 9.0 was used to find the root of the function, f(x)=x-cosx on a close interval [0,1] using the Bisection method, the Newton's method and the Secant method and the result compared. It was observed that the Bisection method converges at the 52 second iteration while Newton and Secant methods converge to the exact root of 0.739085 with error 0.000000 at the 8 th and 6 th iteration respectively. It was then concluded that of the three methods considered, Secant method is the most effective scheme. This is in line with the result in our Ref. .

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Comparative Study of Bisection and Newton-Rhapson Methods of Root-Finding Problems

mekele

This paper presents two numerical techniques of root-finding problems of a non-linear equations with the assumption that a solution exists, the rate of convergence of Bisection method and Newton-Rhapson method of root-finding is also been discussed. The software package , MATLAB 7.6 was used to find the root of the function, f (x) = cosx − x * exp(x) on a close interval [0, 1] using the Bisection method and Newton's method the result was compared. It was observed that the Bisection method converges at the 14 th iteration while Newton methods converge to the exact root of 0.5718 with error 0.0000 at the 2 nd iteration respectively. It was then concluded that of the two methods considered, Newton's method is the most effective scheme. This is in line with the result in our Ref.[9].

Improvements in the Bisection Method of finding roots of an equation

2014 IEEE International Advance Computing Conference (IACC), 2014

Bisection Method is one of the simplest methods in numerical analysis to find the roots of a non-linear equation. It is based on Intermediate Value Theorem. The algorithm proposed in this paper predicts the optimal interval in which the roots of the function may lie and then applies the bisection method to converge at the root within the tolerance range defined by the user. This algorithm also calculates another root of the equation, if that root lies just outside the range of the interval found.

Hybrid Algorithm Improving Bisection, Regula Falsi, Dekker, Brent Algorithms for Roots of Non-linear Equations

International Journal of Latest Research in Engineering and Technology, 2019

Bisection Method for continuous functions and Newton-Raphson method for differentiable function are widely used for finding zeros of non-linear equations. Numerical techniques are explored when an analytic solution is not obvious. There is no single algorithm that works best for every function. We designed and implemented a new hybrid algorithm that is a dynamic blend of theBisectionand RegulaFalsialgorithms. The experimental results validate that the new algorithm outperforms Bisection,RegulaFalsi, Dekker's and Brent'salgorithms with respect to computational iterations. The new algorithm is guaranteed to find a root and requires fewer computational iterations. It is also observed that the new hybrid algorithm performs better that the Secant algorithm and the Newton-Raphson algorithm.The new algorithm guarantees the reliability of Bisection method and speed of Secant method. The theoretical and empirical evidence shows that the computational complexity of the new algorithm is considerably less than that of the classical algorithms.

Comparative Study of Bisection, Newton, Horner’s Method for Solving Nonlinear Equation

Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse), 2021

The Bisection, Newton and Horner’s method are used to compare the efficiency to solve nonlinear function such as trigonometric, exponential, logarithmic and cubic polynomial function. Although these methods are considered as alternative, the methods also possess error compared to the exact value. The efficiency is measured by the error produced at the fixed iteration. The methods are converted into C language and executed by using maple 18.

Blended Root Finding Algorithm Outperforms Bisection and Regula Falsi Algorithms

Mathematics, 2019

Finding the roots of an equation is a fundamental problem in various fields, including numerical computing, social and physical sciences. Numerical techniques are used when an analytic solution is not available. There is not a single algorithm that works best for every function. We designed and implemented a new algorithm that is a dynamic blend of the bisection and regula falsi algorithms. The implementation results validate that the new algorithm outperforms both bisection and regula falsi algorithms. It is also observed that the new algorithm outperforms the secant algorithm and the Newton–Raphson algorithm because the new algorithm requires fewer computational iterations and is guaranteed to find a root. The theoretical and empirical evidence shows that the average computational complexity of the new algorithm is considerably less than that of the classical algorithms.

A Simple Hybrid Method for Finding the Root of Nonlinear Equations

In this paper, we proposed a simple modification of McDougall and Wotherspoon [11] method for approximating the root of univariate function. Our modification is based on the approximating the derivative in the corrector step of the proposed McDougall and Wotherspoon Newton like method using secant method. Numerical examples demonstrate the efficiency of the proposed method.

Parallel Hybrid Algorithm of Bisection and Newton-Raphson Methods to Find Non-Linear Equations Roots

2015

In this paper a new parallel Hybrid algorithm is introduced which is based on the Bisection algorithm and Newton-Raphson algorithm. The proposed Hybrid algorithms helps in finding real roots of single non-linear equations in less number of iterative operations and reduce the time of solving. These methods have been applied in parallel environment. A description of the algorithms details and comparison between them is included in this work.

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