Multi-objective hybrid optimization for micro strip patch antenna design

IF 0.2 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Web Intelligence Pub Date : 2023-08-02 DOI:10.3233/web-220112
Samuyelu Bommu, R. R, Y. Chincholkar, U. L. Mohite
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Abstract

Due to their low price, light weights, as well as simple installation, Micro strip Patch Antennas (MPAs) have been made to perform in a double and multi-band applications. The MP receiver is created with an Electromagnetic Band Gap (EBG) structure in order to decrease the micro strip patch cross-polarized radiation but also achieve the crucial radiation criteria. The polymeric liquid crystals substratum is employed to decrease raw material costs, and also the applicable shape framework are employed to enhance receiver execution. We have established a new optimization based method which has two operating stages. In the begining stage, we have designed a Micro strip patch antenna with certain parameters. Afterwards, these design parameters length, width, height, substrate thickness under area such as get optimized by the newly introduced Battle Royale Customized Spider Monkey Optimization (BRCSMO) algorithm in order to get an antenna with higher performance. We have evaluated the proposed method with regard to measures like receiver profit, productivity, bandwidth, decline loss as well as Total Active Reflection coefficient (TARC) and the outcomes showed that this proposed technique can offer superior outcomes than other approaches.
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微带贴片天线设计的多目标混合优化
由于其价格低,重量轻,以及简单的安装,微带贴片天线(MPAs)已经在双频段和多频段应用中发挥作用。为了减少微带贴片交叉极化辐射,同时达到关键的辐射标准,采用电磁带隙(EBG)结构创建了MP接收机。采用聚合物液晶基板以降低原材料成本,并采用适用的形状框架以提高接收器的执行力。我们建立了一种新的基于优化的方法,该方法分为两个操作阶段。在初始阶段,我们设计了具有一定参数的微带贴片天线。然后,利用新引入的BRCSMO (Battle Royale Customized Spider Monkey Optimization)算法对天线的长度、宽度、高度、衬底厚度等设计参数进行优化,得到性能更高的天线。我们对所提出的方法进行了评估,包括接收器利润、生产率、带宽、衰减损失以及总主动反射系数(TARC)等指标,结果表明,所提出的技术可以提供比其他方法更好的结果。
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来源期刊
Web Intelligence
Web Intelligence COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
0.90
自引率
0.00%
发文量
35
期刊介绍: Web Intelligence (WI) is an official journal of the Web Intelligence Consortium (WIC), an international organization dedicated to promoting collaborative scientific research and industrial development in the era of Web intelligence. WI seeks to collaborate with major societies and international conferences in the field. WI is a peer-reviewed journal, which publishes four issues a year, in both online and print form. WI aims to achieve a multi-disciplinary balance between research advances in theories and methods usually associated with Collective Intelligence, Data Science, Human-Centric Computing, Knowledge Management, and Network Science. It is committed to publishing research that both deepen the understanding of computational, logical, cognitive, physical, and social foundations of the future Web, and enable the development and application of technologies based on Web intelligence. The journal features high-quality, original research papers (including state-of-the-art reviews), brief papers, and letters in all theoretical and technology areas that make up the field of WI. The papers should clearly focus on some of the following areas of interest: a. Collective Intelligence[...] b. Data Science[...] c. Human-Centric Computing[...] d. Knowledge Management[...] e. Network Science[...]
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