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Simulated-annealing-based genetic algorithm for modeling the optical constants of solids

机译:基于模拟退火的遗传算法,对固体的光学常数建模

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We propose a simulated-annealing-based genetic algorithm for solving model parameter estimation problems. The algorithm incorporates advantages of both genetic algorithms and simulated annealing. Tests on computer-generated synthetic data that closely resemble optical constants of a metal were performed to compare the efficiency of plain genetic algorithms against the simulated-annealing-based genetic algorithms. These tests assess the ability of the algorithms to and the global minimum and the accuracy of values obtained for model parameters. Finally, the algorithm with the best performance is used to fit the model dielectric function to data for platinum and aluminum. (C) 1997 Optical Society of America.
机译:我们提出了一种基于模拟退火的遗传算法来解决模型参数估计问题。该算法结合了遗传算法和模拟退火的优点。对计算机生成的与金属的光学常数非常相似的合成数据进行了测试,以比较普通遗传算法与基于模拟退火的遗传算法的效率。这些测试评估了算法的能力以及全局最小值和为模型参数获得的值的准确性。最后,使用性能最佳的算法将模型介电函数与铂和铝的数据拟合。 (C)1997年美国眼镜学会。

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