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Inverse radiation analysis of a one-dimensional participating slab by stochastic particle swarm optimizer algorithm

机译:一维参与平板反辐射分析的随机粒子群优化算法

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摘要

A stochastic particle swarm optimizer (SPSO) algorithm, which can guarantee the convergence of the global optimization solution with probability one, is adopted to estimate the parameters of radiation system. To illustrate the performance of this algorithm, three cases are investigated, in which the source term, the extinction coefficient, the scattering coefficient, and the non-uniform absorption coefficients in a one-dimensional slab are retrieved. The directional radiative intensity, reflectance and transmittance, radiative flux simulated by discrete ordinate method (DOM) are served as input for the inverse analysis, respectively. By SPSO algorithm presented, all these radiative parameters could be estimated accurately, even with noisy data. In conclusion, the SPSO algorithm is proved to be fast and robust, which has the potential to be implemented in various fields of inverse radiation problem.
机译:采用随机粒子群优化算法(SPSO)估计辐射系统的参数,该算法可以保证全局优化解的概率为1。为了说明该算法的性能,研究了三种情况,其中检索了源项,消光系数,散射系数和一维平板中的非均匀吸收系数。通过离散纵坐标法(DOM)模拟的定向辐射强度,反射率和透射率以及辐射通量分别用作反分析的输入。通过提出的SPSO算法,即使有嘈杂的数据,所有这些辐射参数也可以准确估计。总而言之,SPSO算法被证明是快速且健壮的,具有在反辐射问题的各个领域中实现的潜力。

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