The numerical methods for differential equation solution allow obtaining a discrete field that converges towards the solution if the method is applied to the correct problem. Nevertheless, the numerical methods have the restricted class of the equations, on which the convergence with a given parameter set or range is proved. Only a few "cheap and dirty" numerical methods converge on a wide class of equations without parameter tuning with the lower approximation order price. The article presents a method that uses an optimization algorithm to obtain a solution using the parameterized approximation. The result may not be as precise as an expert one. However, it allows solving the wide class of equations in an automated manner without the algorithm's parameters change.
翻译:差异方程式解决方案的数值方法允许获得一个离散字段,如果该方法适用于正确的问题,该字段会与解决方案相趋同。然而,数字方法具有方程式的有限类别,可以证明与特定参数集或范围的趋同。只有少数“廉价和肮脏”的数值方法在不与较低近似定价调和参数的广类方程式上趋同。文章提出了一个方法,使用优化算法获得使用参数近似值的解决方案。结果可能不如专家精确。然而,它允许在不改变算法参数的情况下以自动方式解决大类方程式。