What is the best numerical method for

In summary, the best numerical methods for solving differential equations, optimization problems, interpolation and extrapolation, systems of linear equations, and numerical integration all depend on the specific problem and its constraints. Some commonly used methods include Euler's method, Runge-Kutta methods, finite difference methods, gradient descent, Newton's method, genetic algorithms, Lagrange interpolation, Newton's divided difference method, spline interpolation, Gaussian elimination, LU decomposition, Jacobi or Gauss-Seidel iterative methods, the trapezoidal rule, Simpson's rule, and Gaussian quadrature.
  • #1
hunt_mat
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An equation of the form:
[tex]
\frac{\partial A}{\partial t}+\frac{\partial B}{\partial x}=C
[/tex]
I am thinking Lax-Wendroff.
 
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  • #2
I would think so, seeing as how it fits the Wikipedia example fairly well.
 
  • #3
I have been thinking about this, would I have to define:
[tex]
C=\frac{\partial}{\partial x}\int Cdx
[/tex]
and then define
[tex]
B'=B-\int Cdx
[/tex]
to get
[tex]
\frac{\partial A}{\partial t}+\frac{\partial B'}{\partial x}=0
[/tex]
and then apply Lax-Wendroff to the above equation?
 

Related to What is the best numerical method for

What is the best numerical method for solving differential equations?

The best numerical method for solving differential equations depends on the specific type of differential equation and its boundary conditions. Some commonly used methods include Euler's method, Runge-Kutta methods, and finite difference methods.

What is the best numerical method for optimization problems?

The best numerical method for optimization problems also depends on the specific problem and its constraints. Some commonly used methods include gradient descent, Newton's method, and genetic algorithms.

What is the best numerical method for interpolation and extrapolation?

The best numerical method for interpolation and extrapolation depends on the type of data and the level of accuracy required. Some commonly used methods include Lagrange interpolation, Newton's divided difference method, and spline interpolation.

What is the best numerical method for solving systems of linear equations?

The best numerical method for solving systems of linear equations depends on the size and structure of the system. Some commonly used methods include Gaussian elimination, LU decomposition, and iterative methods such as Jacobi or Gauss-Seidel.

What is the best numerical method for numerical integration?

The best numerical method for numerical integration also depends on the specific function being integrated and the desired level of accuracy. Some commonly used methods include the trapezoidal rule, Simpson's rule, and Gaussian quadrature.

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