Evaluation of genetic algorithms, particle swarm optimisation, and firefly algorithms in antenna design

2016 13th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD) Pub Date : 2016-06-27 DOI:10.1109/SMACD.2016.7520747

H. J. Mohammed, F. Abdulsalam, A. S. Abdulla, R. Ali, R. Abd‐Alhameed, J. Noras, Y. Al-Yasir, A. Ali, Jonathan Rodriguez, Abdelgader M. Abdalla

引用次数: 24

Abstract

Evolutionary optimization techniques with multiple objectives are applied to the design of microstrip antennas. The biologically inspired algorithms, Particle Swarm Optimization, Genetic Algorithms and the Firefly Algorithm, are integrated in new software, Antenna Optimizer, which combines attributes of the electromagnetic design environment of CST Microwave Studio with those of the technical computing and programming environment of MATLAB. Impedance matching and gain improvement are optimized over a predefined frequency range, resulting in a very small and compact 12 mm × 21 mm ultra-wideband antenna which was fabricated and measured.

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天线设计中遗传算法、粒子群优化和萤火虫算法的评估

将多目标进化优化技术应用于微带天线的设计。该软件结合了CST Microwave Studio的电磁设计环境和MATLAB的技术计算和编程环境的特性，将受生物学启发的算法，粒子群优化算法，遗传算法和萤火虫算法集成在新的软件Antenna Optimizer中。在预定义的频率范围内优化阻抗匹配和增益改进，从而制作和测量了一个非常小且紧凑的12 mm × 21 mm超宽带天线。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2016 13th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD)

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