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Optimization Design of Metamaterial Absorbers Based on an Improved Adaptive Genetic Algorithm

机译:基于改进自适应遗传算法的超材料吸收器的优化设计

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摘要

Most reported metamaterials are designed empirically by parameter sweep, which is time-consuming and ineffective. We propose an optimization method of designing metamaterial absorbers based on an improved adaptive genetic algorithm (IAGA), with the aim to get wideband absorption. Firstly, an IAGA optimization model is presented, of which the crossover probability is adaptively adjusted by introducing a nonlinear function, and the mutation probability is adaptively adjusted using complementary idea. Then, a wideband triple-layer metamaterial absorber in THz region is designed and optimized using IAGA, getting about 40.4% increasing of relative bandwidth compared with the results of reference [19]. A further comparison between IAGA and standard genetic algorithm (SGA) indicates that the IAGA is an effective method in improving convergence speed and stability, and can be used to optimize structure parameters of metamaterial absorbers with desired characteristics.
机译:大多数报告的超材料都是通过参数扫描以经验方式设计的,这既费时又无效。我们提出了一种基于改进的自适应遗传算法(IAGA)设计超材料吸收体的优化方法,旨在获得宽带吸收。首先,提出了一种IAGA优化模型,通过引入非线性函数来自适应地调整交叉概率,并利用互补思想来自适应地调整突变概率。然后,使用IAGA对THz区域的宽带三层超材料吸收器进行了设计和优化,与参考结果相比,相对带宽增加了约40.4%[19]。 IAGA与标准遗传算法(SGA)的进一步比较表明,IAGA是提高收敛速度和稳定性的有效方法,可用于优化具有所需特性的超材料吸收体的结构参数。

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