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  2. Runge–Kutta methods - Wikipedia

    en.wikipedia.org/wiki/RungeKutta_methods

    RungeKutta–Nyström methods are specialized RungeKutta methods that are optimized for second-order differential equations. [22] [23] A general RungeKutta–Nyström method for a second-order ODE system ¨ = (,, …,) with order is with the form

  3. Heun's method - Wikipedia

    en.wikipedia.org/wiki/Heun's_method

    It is named after Karl Heun and is a numerical procedure for solving ordinary differential equations (ODEs) with a given initial value. Both variants can be seen as extensions of the Euler method into two-stage second-order RungeKutta methods. The procedure for calculating the numerical solution to the initial value problem:

  4. List of Runge–Kutta methods - Wikipedia

    en.wikipedia.org/wiki/List_of_RungeKutta_methods

    The RungeKutta–Fehlberg method has two methods of orders 5 and 4; it is sometimes dubbed RKF45 . Its extended Butcher Tableau is: / / / / / / / / / / / / / / / / / / / / / / / / / / The first row of b coefficients gives the fifth-order accurate solution, and the second row has order four.

  5. Linear multistep method - Wikipedia

    en.wikipedia.org/wiki/Linear_multistep_method

    Single-step methods (such as Euler's method) refer to only one previous point and its derivative to determine the current value. Methods such as RungeKutta take some intermediate steps (for example, a half-step) to obtain a higher order method, but then discard all previous information before taking a second step. Multistep methods attempt ...

  6. Numerical methods for ordinary differential equations - Wikipedia

    en.wikipedia.org/wiki/Numerical_methods_for...

    Explicit examples from the linear multistep family include the Adams–Bashforth methods, and any RungeKutta method with a lower diagonal Butcher tableau is explicit. A loose rule of thumb dictates that stiff differential equations require the use of implicit schemes, whereas non-stiff problems can be solved more efficiently with explicit ...

  7. Trapezoidal rule (differential equations) - Wikipedia

    en.wikipedia.org/wiki/Trapezoidal_rule...

    In numerical analysis and scientific computing, the trapezoidal rule is a numerical method to solve ordinary differential equations derived from the trapezoidal rule for computing integrals. The trapezoidal rule is an implicit second-order method, which can be considered as both a RungeKutta method and a linear multistep method.

  8. Euler method - Wikipedia

    en.wikipedia.org/wiki/Euler_method

    For this reason, the Euler method is said to be a first-order method, while the midpoint method is second order. We can extrapolate from the above table that the step size needed to get an answer that is correct to three decimal places is approximately 0.00001, meaning that we need 400,000 steps.

  9. Runge–Kutta method (SDE) - Wikipedia

    en.wikipedia.org/wiki/RungeKutta_method_(SDE)

    A newer RungeKutta scheme also of strong order 1 straightforwardly reduces to the improved Euler scheme for deterministic ODEs. [2] Consider the vector stochastic process () that satisfies the general Ito SDE = (,) + (,), where drift and volatility are sufficiently smooth functions of their arguments.