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A Gaussian RBFs method with regularization for the numerical solution of inverse heat conduction problems

机译:逆导热问题数值解的带正则化的高斯RBFs方法

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摘要

In this paper, a recursion numerical technique is considered to solve the inverse heat conduction problems, with an unknown time-dependent heat source and the Neumann boundary conditions. The numerical solutions of the heat diffusion equations are constructed using the Gaussian radial basis functions. The details of algorithms in the one-dimensional and two-dimensional cases, involving the global or partial initial conditions, are proposed, respectively. The Tikhonov regularization method, with the generalized cross-validation criterion, is used to obtain more stable numerical results, since the linear systems are badly ill-conditioned. Moreover, we propose some results of the condition number estimates to a class of positive define matrices constructed by the Gaussian radial basis functions. Some numerical experiments are given to show that the presented schemes are favourably accurate and effective.
机译:本文考虑了一种递归数值技术,以解决未知时变热源和诺伊曼边界条件的逆导热问题。利用高斯径向基函数构造了热扩散方程的数值解。分别提出了一维和二维情况下涉及全局或部分初始条件的算法的细节。带有广义交叉验证准则的Tikhonov正则化方法用于获得更稳定的数值结果,因为线性系统的病态严重。此外,我们对由高斯径向基函数构造的一类正定义矩阵提出了条件数估计的一些结果。数值实验表明,所提出的方案准确,有效。

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