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首页> 外文期刊>International Journal of Heat and Mass Transfer >Performance comparison of particle swarm optimization and genetic algorithm for inverse surface radiation problem
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Performance comparison of particle swarm optimization and genetic algorithm for inverse surface radiation problem

机译：粒子群算法和遗传算法求解逆表面辐射问题的性能比较

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摘要

The heat transfer mechanism of thermal radiation is directly related to either the emission and propagation of electromagnetic waves or the transport of photons. Depending on the participation of the medium in space, thermal radiation can be classified into two forms, which are surface and gas radiation, respectively. In the present study, unknown surface radiation properties are estimated by an inverse analysis for a surface radiation in an axisymmetric cylindrical enclosure. For efficiency, the repulsive particle swarm optimization (RPSO) algorithm, which showed an outstanding effectiveness in the previous inverse gas radiation problem, is adopted as an inverse solver. By comparing the convergence rates of an objective function and the estimated accuracies with the results of the hybrid genetic algorithm (HGA) and the particle swarm optimization (PSO) method, the performance of the RPSO algorithm is verified to be quite an efficient method as the inverse solver when applied to the retrieval of unknown properties of the surface radiation problem.
机译：热辐射的热传递机制与电磁波的发射和传播或光子的传输直接相关。根据介质在空间中的参与情况，热辐射可以分为两种形式，分别是表面辐射和气体辐射。在本研究中，通过对轴对称圆柱外壳中的表面辐射进行反分析来估计未知的表面辐射特性。为了提高效率，采用了排斥粒子群优化（RPSO）算法作为逆求解器，该算法在先前的逆向气体辐射问题中显示了出色的有效性。通过将目标函数的收敛速度和估计的准确性与混合遗传算法（HGA）和粒子群优化（PSO）方法的结果进行比较，验证了RPSO算法的性能是一种非常有效的方法。逆求解器应用于表面辐射问题的未知属性的检索时。

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