Recently developed social-based algorithms for antennas optimization

F. Grimaccia, M. Mussetta, A. Niccolai, P. Pirinoli, R. Zich
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引用次数: 9

Abstract

In recent years there has been an increasing attention to novel evolutionary optimization techniques employed to engineering and real-world applications. Among these, the design of antennas and electromagnetic devices is a well-established field of application. This paper presents a new population based algorithm inspired by the recent explosion of social networks and their capability to drive people's decision making process in everyday life. Early experimental studies have already proven its effectiveness in the optimized design of EM structures. Here this optimization procedure called SNO - Social Network Optimization is presented and tested in a first comparative study to prove its effectiveness and performance compared with traditional evolutionary algorithms.
最近开发了基于社交的天线优化算法
近年来,人们越来越关注应用于工程和实际应用的新型进化优化技术。其中,天线和电磁器件的设计是一个成熟的应用领域。本文提出了一种新的基于人口的算法,其灵感来自于最近社交网络的爆炸式增长及其驱动人们日常生活决策过程的能力。早期的实验研究已经证明了它在电磁结构优化设计中的有效性。本文提出了一种称为SNO - Social Network optimization的优化过程,并在第一次比较研究中进行了测试,以证明其与传统进化算法相比的有效性和性能。
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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