Analysis and Comparative Study of Numerical Solutions of Initial Value Problems (IVP) in Ordinary Differential Equations (ODE) With Euler and Runge Kutta Methods (original) (raw)

A Comparative Study on Numerical Solutions of Initial Value Problems (IVP) for Ordinary Differential Equations (ODE) with Euler and Runge Kutta Methods

This paper mainly presents Euler method and fourth‐order Runge Kutta Method (RK4) for solving initial value problems (IVP) for ordinary differential equations (ODE). The two proposed methods are quite efficient and practically well suited for solving these problems. In order to verify the ac‐ curacy, we compare numerical solutions with the exact solutions. The numerical solutions are in good agreement with the exact solutions. Numerical comparisons between Euler method and Runge Kutta method have been presented. Also we compare the performance and the computa‐ tional effort of such methods. In order to achieve higher accuracy in the solution, the step size needs to be very small. Finally we investigate and compute the errors of the two proposed meth‐ ods for different step sizes to examine superiority. Several numerical examples are given to dem‐ onstrate the reliability and efficiency.

A Comparative Investigation on Numerical Solution of Initial Value Problem by Using Modified Euler's Method and Runge- Kutta Method

IOSR Journals , 2019

In this article, Modified Euler's Method and Runge-Kutta Methods have been used to find the numerical solutions of ordinary differential equations with initial value problems. By using MATLAB we determined the solutions of some numerical problems and at the same time calculated the exact analytic solution. Then, the numerical approximate solutions were compared with the exact solutions for validating the accuracy. We found that, the solution become more precise when the step size is very small. Here, the difference between the numerical approximate solutions and analytic solutions is the relative error. We found that, between the two proposed methods the relative error is nominal for Runge-Kutta fourth order method.

Numerical Solution of First Order Ordinary Differential Equation by Using Runge-Kutta Method

International Journal of Systems Science and Applied Mathematics, 2021

In this paper, the classical fourth-order Runge-Kutta methodis presented for solving the first-order ordinary differential equation. First, the given solution domain is discretizedby using a uniform discretization grid point. Next by applyingthe forward difference method, we discretized the given ordinary differential equation. And formulating a difference equation. Then using this difference equation, the given first-order ordinary differential equation is solved by using the classicalfourth-order Runge-Kutta method at each specified grid point. To validate the applicability of the proposed method, two model examples are considered and solved at each specific grid point on its solution domain. The stability and convergent analysis of the present method is worked by supportedthe theoretical and mathematical statementsand the accuracy of the solution is obtained. The accuracy of the present methodhas been shown in the sense ofmaximumabsolute error and the local behavior of the solution is captured exactly. Numerical and exact solutions have been presented in tables and graphs and the corresponding maximumabsolute errorisalso presented in tables and graphs. The present method approximates the exact solution very well and it is quite efficient and practically well suitedfor solving first-order ordinary differential equations. The numerical result presented in tables and graphsindicates that the approximate solution is in good agreement with the exact solution. Hence the proposed method is accruable to solve ordinary differential equations.

Study of Numerical Solution of Fourth Order Ordinary Differential Equations by fifth order Runge-Kutta Method

International Journal of Scientific Research in Science, Engineering and Technology, 2019

In this paper we present fifth order Runge-Kutta method (RK5) for solving initial value problems of fourth order ordinary differential equations. In this study RK5 method is quite efficient and practically well suited for solving boundary value problems. All mathematical calculation performed by MATLAB software for better accuracy and result. The result obtained, from numerical examples, shows that this method more efficient and accurate. These methods are preferable to some existing methods because of their simplicity, accuracy and less computational cost involved.

Numerical Computations of General Non-Linear Second Order Initial Value Problems by Using Modified Runge-Kutta Method

Matrix Science Mathematic

Numerical solution of ordinary differential equations is the most important technique which is widely used for mathematical modelling in science and engineering. The differential equation that describes the problem is typically too complex to precisely solve in real-world circumstances. Since most ordinary differential equations are not solvable analytically, numerical computations are the only way to obtain information about the solution. Many different methods have been proposed and used is an attempt to solve accurately various types of ordinary differential equations. Among them, Runge-Kutta is a well-known and popular method because of their good efficiency. This paper contains an analysis for the computations of the modified Runge-Kutta method for nonlinear second order initial value problems. This method is wide quite efficient and practically well suited for solving linear and non-linear problems. In order to verify the accuracy, we compare numerical solution with the exact ...

Comparison of Higher Order Taylor's Method and Runge- Kutta Methods for Solving First Order Ordinary Differential Equations

This paper mainly present, sixth order Taylor's method and fifth order Runge-Kutta method (RK5) for solving initial value problems of first order ordinary differential equations. The two proposed methods are quite efficient and practically well suited for solving these problems. In order to verify the accuracy, we compare numerical solutions with the exact solutions. The numerical solutions are in good agreement with the exact solutions. Numerical comparisons between Taylor's method and Runge-Kutta methods have been presented. The stability and convergence of the methods have been investigated. Two model examples (linear and non-linear) are given to demonstrate the reliability and efficiency of the methods. Point wise absolute errors are obtained by using MATLAB software. The proposed methods also compared with the existing literatures (RK4) and shows betterment results.

Numerical comparison by different methods (second order Runge Kutta methods, Heun method, fixed point method and Ralston method) to differential equations with initial condition

Scientia et Technica

This manuscript contains a detailed comparison between numerical solution methods of ordinary differential equations, which start from the Taylor series method of order 2, stating that this series hinders calculations for higher order derivatives of functions of several variables, so that the Runge Kutta methods of order 2 are implemented, which achieve the required purpose avoiding the cumbersome calculations of higher order derivatives. In this document, different variants of the Runge-Kutta methods of order 2 will be exposed from an introduction and demonstration of the connection of these with the Taylor series of order 2, these methods are: the method of Heun, the method of midpoint and the Ralston method. It will be observed from the solution of test differential equations its respective error with respect to the analytical solution, obtaining an error index dictated by the mean square error EMC. Through this document we will know the best numerical approximation to the analyt...

NUMERICAL COMPARISON OF VARIOUS ORDER EXPLICIT RUNGE KUTTA METHODS WITH MATLAB ODE SOLVER

Asian Journal of Mathematics and Computer Research, 2018

The purpose of this paper is, to study the numerical computation of ordinary differential equation and to show the details of implementing a few steps of Explicit RungeKutta methods, as well as how to use built-in functions available in MATLAB (2009a). In the first part, we use some Explicit RungeKutta methods to introduce the basic ideas associated with initial value problems (IVP). In the second part, we use the Runge-Kutta method and Runge-Kutta Fehlberg method presented together with the built-in MATLAB solver Ode45.The implementations that we develop in this paper are designed to build intuition and are the first step from textbook formula on ode to production software. Numerical example is given to illustrate the accuracy and robustness of these numerical methods.