Oppositely converging Newton-Raphson method for non-linear equilibrium problems

2009 ◽  
Vol 79 (3) ◽  
pp. 375-378 ◽  
Author(s):  
Isaac Fried
Keyword(s):  
Equilibrium Problems ◽  
Non Linear ◽  
Newton Raphson ◽  
Raphson Method

Comparative Study of Iterative Methods for Solving Non-Linear Equations

2021 ◽  
Vol 23 (07) ◽  
pp. 858-866
Author(s):  
Gauri Thakur ◽  
◽  
J.K. Saini ◽  
Keyword(s):  
Numerical Analysis ◽  
Iterative Methods ◽  
Linear Equations ◽  
Bisection Method ◽  
Practical Applications ◽  
Non Linear ◽  
False Position ◽  
Newton Raphson ◽  
Raphson Method ◽  
Non Linear Equations

In numerical analysis, methods for finding roots play a pivotal role in the field of many real and practical applications. The efficiency of numerical methods depends upon the convergence rate (how fast the particular method converges). The objective of this study is to compare the Bisection method, Newton-Raphson method, and False Position Method with their limitations and also analyze them to know which of them is more preferred. Limitations of these methods have allowed presenting the latest research in the area of iterative processes for solving non-linear equations. This paper analyzes the field of iterative methods which are developed in recent years with their future scope.

scholarly journals SOLVING COCOA POD SIGMOID GROWTH MODEL WITH NEWTON RAPHSON METHOD

2012 ◽  
Vol 09 ◽  
pp. 44-51
Author(s):  
ALBERT LING SHENG CHANG ◽  
NAVIES MAISIN
Keyword(s):  
Growth Model ◽  
Morphological Characteristics ◽  
Growth Period ◽  
Growth Function ◽  
Growth Data ◽  
Non Linear ◽  
Newton Raphson ◽  
Pod Length ◽  
Raphson Method ◽  
Pod Growth

Cocoa pod growth modelling are useful in crop management, pest and disease management and yield forecasting. Recently, the Beta Growth Function has been used to determine the pod growth model due to its unique for the plant organ growth which is zero growth rate at both the start and end of a precisely defined growth period. Specific pod size (7cm to 10cm in length) is useful in cocoa pod borer (CPB) management for pod sleeving or pesticide spraying. The Beta Growth Function is well-fitted to the pods growth data of four different cocoa clones under non-linear function with time (t) as its independent variable which measured pod length and diameter weekly started at 8 weeks after fertilization occur until pods ripen. However, the same pod length among the clones did not indicate the same pod age since the morphological characteristics for cocoa pods vary among the clones. Depending on pod size for all the clones as guideline in CPB management did not give information on pod age, therefore it is important to study the pod age at specific pod sizes on different clones. Hence, Newton Raphson method is used to solve the non-linear equation of the Beta Growth Function of four different group of cocoa pod at specific pod size.

Non-Linear Static Analysis of 2D Steep Wave Riser Under Current Load

2016 ◽  
Author(s):  
Hongdong Qiao ◽  
Weidong Ruan ◽  
Zhaohui Shang ◽  
Yong Bai
Keyword(s):  
Finite Difference ◽  
Finite Difference Method ◽  
Differential Equations ◽  
Ordinary Differential Equations ◽  
Difference Method ◽  
Shooting Method ◽  
Non Linear ◽  
Newton Raphson ◽  
Raphson Method ◽  
Steep Wave

A new solution combining finite difference method and shooting method is developed to analyze the behavior of steep wave riser subjected to current loading. Based on the large deformation beam theory and mechanics equilibrium principle, a set of non-linear ordinary differential equations describing the motion of the steep wave riser are obtained. Then, finite difference method and shooting method are adopted and combined to solve the ordinary differential equations with zero moment boundary conditions at both the seabed end and surface end of the steep wave riser. The resulting non-linear finite difference formulations can be solved effectively by Newton-Raphson method. To improve iterative efficiency, shooting method is also employed to obtain the initial value for Newton-Raphson method. Results are compared with that of FEM by OrcaFlex, to verify the accuracy and reliability of the numerical method. Finally, a series of sensitivity analyses are also performed to highlight the influencing parameters in the steep wave riser.

scholarly journals Perbandingan Metode Newton-Raphson & Metode Secant Untuk Mencari Akar Persamaan Dalam Sistem Persamaan Non-Linier

Petir ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 72-79
Author(s):  
Endang Sunandar ◽  
Indrianto Indrianto
Keyword(s):  
Linear Equation ◽  
Numerical Method ◽  
Equation System ◽  
Elimination Method ◽  
Non Linear Equation ◽  
Linear Equation System ◽  
Non Linear ◽  
Mathematical Problems ◽  
Newton Raphson ◽  
Raphson Method

The numerical method is a technique used to formulate mathematical problems so that it can be solved using ordinary arithmetic operations. In general, numerical methods are used to solve mathematical problems that cannot be solved by ordinary analytic methods. In the Numerical Method, we recognize two types of systems of equations, namely the Linear Equation System and the Non-Linear Equation System. Each system of equations has several methods. In the Linear Equation System between methods is the Gauss Elimination method, the Gauss-Jordan Elimination method, the LU (Lower-Upper) Decomposition method. And for Non-Linear Equation Systems between the methods are the Bisection method, the Regula Falsi method, the Newton Raphson method, the Secant method, and the Fix Iteration method. In this study, researchers are interested in analyzing 2 methods in the Non-Linear Equation System, the Newton-Raphson method and the Secant method. And this analysis process uses the Java programming language tools, this is to facilitate the analysis of method completion algorithm, and monitoring in terms of execution time and analysis of output results. So we can clearly know the difference between what happens between the two methods.

scholarly journals MODIFIED QUADRATURE ITERATED METHODS OF BOOLE RULE AND WEDDLE RULE FOR SOLVING NON-LINEAR EQUATIONS

2021 ◽  
Vol 16 (2) ◽  
Author(s):  
Umair Khalid Qureshi
Keyword(s):  
Applied Sciences ◽  
Linear Equations ◽  
Numerical Results ◽  
Graphical Representations ◽  
Quadrature Method ◽  
Non Linear ◽  
Newton Raphson ◽  
Steffensen Method ◽  
Raphson Method ◽  
Non Linear Equations

This article is presented a modified quadrature iterated methods of Boole rule and Weddle rule for solving non-linear equations which arise in applied sciences and engineering. The proposed methods are converged quadratically and the idea of developed research comes from Boole rule and Weddle rule. Few examples are demonstrated to justify the proposed method as the assessment of the newton raphson method, steffensen method, trapezoidal method, and quadrature method. Numerical results and graphical representations of modified quadrature iterated methods are examined with C++ and EXCEL. The observation from numerical results that the proposed modified quadrature iterated methods are performance good and well executed as the comparison of existing methods for solving non-linear equations.

scholarly journals Wilkinson Polynomials: Accuracy Analysis Based on Numerical Methods of the Taylor Series Derivative

2020 ◽  
Vol 3 (2) ◽  
pp. 155-160
Author(s):  
Vera Mandailina ◽  
Syaharuddin Syaharuddin ◽  
Dewi Pramita ◽  
Malik Ibrahim ◽  
Habib Ratu Perwira Negara
Keyword(s):  
Taylor Series ◽  
Linear Equations ◽  
Computational Design ◽  
Qualitative Comparison ◽  
Comparison Results ◽  
Starting Point ◽  
Non Linear ◽  
Newton Raphson ◽  
Raphson Method ◽  
Non Linear Equations

Some of the numeric methods for solutions of non-linear equations are taken from a derivative of the Taylor series, one of which is the Newton-Raphson method. However, this is not the only method for solving cases of non-linear equations. The purpose of the study is to compare the accuracy of several derivative methods of the Taylor series of both single order and two-order derivatives, namely Newton-Raphson method, Halley method, Olver method, Euler method, Chebyshev method, and Newton Midpoint Halley method. This research includes qualitative comparison types, where the simulation results of each method are described based on the comparison results. These six methods are simulated with the Wilkinson equation which is a 20-degree polynomial. The accuracy parameters used are the number of iterations, the roots of the equation, the function value f (x), and the error. Results showed that the Newton Midpoint Halley method was the most accurate method. This result is derived from the test starting point value of 0.5 to the equation root x = 1, completed in 3 iterations with a maximum error of 0.0001. The computational design and simulation of this iterative method which is a derivative of the two-order Taylor series is rarely found in college studies as it still rests on the Newton-Raphson method, so the results of this study can be recommended in future learning.

scholarly journals AN ITERATIVE, BRACKETING & DERIVATIVE-FREE METHOD FOR NUMERICAL SOLUTION OF NON-LINEAR EQUATIONS USING STIRLING INTERPOLATION TECHNIQUE

2021 ◽  
Author(s):  
Sanaullah Jamali
Keyword(s):  
Linear Equations ◽  
Derivative Free ◽  
Interpolation Technique ◽  
Non Linear ◽  
Derivative Free Method ◽  
Newton Raphson ◽  
Microsoft Windows ◽  
Regula Falsi Method ◽  
Raphson Method ◽  
Non Linear Equations

In this article, an iterative, bracketing and derivative-free method have been proposed with the second-order of convergence for the solution of non-linear equations. The proposed method derives from the Stirling interpolation technique, Stirling interpolation technique is the process of using points with known values or sample points to estimate values at unknown points or polynomials. All types of problems (taken from literature) have been tested by the proposed method and compared with existing methods (regula falsi method, secant method and newton raphson method) and it’s noted that the proposed method is more rapidly converges as compared to all other existing methods. All problems were solved by using MATLAB Version: 8.3.0.532 (R2014a) on my personal computer with specification Intel(R) Core (TM) i3-4010U CPU @ 1.70GHz with RAM 4.00GB and Operating System: Microsoft Windows 10 Enterprise Version 10.0, 64-Bit Server, x64-based processor.

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