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Estimation of unknown heat source function in inverse heat conduction problems using quantum-behaved particle swarm optimization

机译:用量子行为粒子群算法估计逆热传导问题中的未知热源函数

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摘要

The estimation of temporal dependent heat source in transient heat conduction problem is investigated. A stochastic method known as quantum-behaved particle swarm optimization (QPSO) is used to estimate the heat source without a priori information on its functional form, which is classified as the function estimation by inverse calculation. Because of the ill-posedness of this kind of inverse problems, Tikhonov regularization method is applied in this paper to stabilize the solution. Numerical experiments indicate the validity and stability of the QPSO method. Comparison with the conjugate gradient method (CGM) is also presented in this paper.
机译:研究了瞬态热传导问题中随时间变化的热源的估计。一种称为量子行为粒子群优化(QPSO)的随机方法用于估计热源,而无需关于其功能形式的先验信息,该方法通过逆计算被归类为功能估计。由于这类反问题的不适定性,本文采用Tikhonov正则化方法来稳定解。数值实验表明了QPSO方法的有效性和稳定性。本文还介绍了与共轭梯度法(CGM)的比较。

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