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Monte Carlo method for solution of initial-boundary value problem for nonlinear parabolic equations

机译:非线性抛物方程初边值问题的蒙特卡罗方法

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In this paper we will consider the initial-boundary value problem for a parabolic equation with a polynomial non-linearity relative to the unknown function. First we will derive a probabilistic representation of our problem. The representation of the solution of this problem is given in the form of a mathematical expectation, which is determined based on trajectories of branching processes. Under the assumption of the existence of the solution, an unbiased estimator is built using trajectories of a branching process. We will use a mean value theorem to write out a special integral equation, that equates the value of the unknown function u(x,t) with its integral over a spheroid and balloid with center at the point (x, t). A probabilistic representation of the solution to the problem in the form of mathematical expectation of some random variables is obtained. This probabilistic representation uses a branching process whose trajectories are used in the contraction of an unbiased estimator for the solution. The derived unbiased estimator has a finite variance, and is built up from trajectories of branching processes with a finite average number of branches. Finally, the results of numerical experiments and application to the practical problems are discussed.
机译:在本文中,我们将考虑相对于未知函数具有多项式非线性的抛物线方程的初边值问题。首先,我们将得出问题的概率表示。该问题的解决方案的表示形式是以数学期望的形式给出的,该期望是基于分支过程的轨迹而确定的。在解决方案存在的假设下,使用分支过程的轨迹构建无偏估计量。我们将使用平均值定理写出一个特殊的积分方程,该方程将未知函数u(x,t)的值与其在点(x,t)处的椭球和椭球上的积分相等。以一些随机变量的数学期望形式获得了问题解决方案的概率表示。该概率表示使用分支过程,该分支过程的轨迹用于解决方案的无偏估计量的收缩中。派生的无偏估计量具有有限方差,并且是由具有有限平均分支数的分支过程的轨迹建立的。最后,讨论了数值实验的结果及其在实际问题中的应用。

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