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  2. Dormand–Prince method - Wikipedia

    en.wikipedia.org/wiki/Dormand–Prince_method

    Dormand–Prince is the default method in the ode45 solver for MATLAB [4] and GNU Octave [5] and is the default choice for the Simulink's model explorer solver. It is an option in Python's SciPy ODE integration library [6] and in Julia's ODE solvers library. [7]

  3. Runge–Kutta–Fehlberg method - Wikipedia

    en.wikipedia.org/wiki/RungeKutta–Fehlberg...

    "New high-order Runge-Kutta formulas with step size control for systems of first and second-order differential equations". Zeitschrift für Angewandte Mathematik und Mechanik . 44 (S1): T17–T29.

  4. List of Runge–Kutta methods - Wikipedia

    en.wikipedia.org/wiki/List_of_RungeKutta_methods

    Again, this Diagonally Implicit RungeKutta method is A-stable if and only if . As the previous method, this method is again L-stable if and only if x {\displaystyle x} equals one of the roots of the polynomial x 2 − 2 x + 1 2 {\textstyle x^{2}-2x+{\frac {1}{2}}} , i.e. if x = 1 ± 2 2 {\textstyle x=1\pm {\frac {\sqrt {2}}{2}}} .

  5. Runge–Kutta methods - Wikipedia

    en.wikipedia.org/wiki/RungeKutta_methods

    All RungeKutta methods mentioned up to now are explicit methods. Explicit RungeKutta methods are generally unsuitable for the solution of stiff equations because their region of absolute stability is small; in particular, it is bounded. [25] This issue is especially important in the solution of partial differential equations.

  6. One-step method - Wikipedia

    en.wikipedia.org/wiki/One-step_method

    The Matlab function ode45 implements a one-step method that uses two embedded explicit Runge-Kutta methods with convergence orders 4 and 5 for step size control. [29] The solution can now be plotted, as a blue curve and as a red curve; the calculated points are marked by small circles:

  7. Adaptive step size - Wikipedia

    en.wikipedia.org/wiki/Adaptive_step_size

    For simplicity, the following example uses the simplest integration method, the Euler method; in practice, higher-order methods such as RungeKutta methods are preferred due to their superior convergence and stability properties. Consider the initial value problem ′ = (, ()), =

  8. 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 ...

  9. Bogacki–Shampine method - Wikipedia

    en.wikipedia.org/wiki/Bogacki–Shampine_method

    The Bogacki–Shampine method is implemented in the ode3 for fixed step solver and ode23 for a variable step solver function in MATLAB (Shampine & Reichelt 1997). Low-order methods are more suitable than higher-order methods like the Dormand–Prince method of order five, if only a crude approximation to the solution is required. Bogacki and ...