Spider Monkey Optimization: A Novel Technique for Antenna Optimization

被引：93

作者：

Al-Azza, Ali A. ^{[1
,2
]}

Al-Jodah, Ammar A. ^{[3
]}

Harackiewicz, Frances J. ^{[1
]}

机构：

[1] So Illinois Univ, Dept Elect & Comp Engn, Carbondale, IL 62901 USA

[2] Univ Basrah, Engn Coll, Dept Elect Engn, Basrah, Iraq

[3] Univ Technol Baghdad, Control & Syst Engn Dept, Baghdad 10053, Iraq

来源：

IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS | 2016年 / 15卷

关键词：

Array antennas; microstrip antenna; optimization methods; spider monkey algorithm; GENETIC ALGORITHMS;

D O I：

10.1109/LAWP.2015.2490103

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The aim of this letter is to introduce and use the spider monkey optimization (SMO) as an optimization technique for the electromagnetics and antenna communities. The SMO is a new swarm intelligence technique that models the foraging behavior of spider monkeys. To show the efficiency of the SMO, different examples are presented, and the results are compared to the results obtained using other popular optimization techniques. The optimization procedure is used to synthesize the array factor of a linear antenna array and to optimally design an E-shaped patch antenna for wireless applications. By comparing to traditional optimization techniques reported in the literature, it is evident that SMO is efficient in reaching the optimum solutions with less number of experiments.

引用

页码：1016 / 1019

页数：4

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