Hybrid Genetic Programming for the Development of Metamaterials Designs With Improved Characteristics

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@Article{Clemens:2018:ieeeAWPL,

• author = "Scott Clemens and Magdy F. Iskander and Zhengqing Yun and Jennifer Rayno",
• journal = "IEEE Antennas and Wireless Propagation Letters",
• title = "Hybrid Genetic Programming for the Development of Metamaterials Designs With Improved Characteristics",
• year = "2018",
• volume = "17",
• number = "3",
• pages = "513--516",
• keywords = "genetic algorithms, genetic programming, Artificial magnetic conductor (AMC), terahertz (THz) absorber",
• DOI = "doi:10.1109/LAWP.2018.2800057",
• ISSN = "1536-1225",
• month = mar,
• abstract = "The expansion of a hybrid genetic program's (HGP) functionality to allow for the development of broadband two-dimensional metamaterials designs with advanced characteristics is presented. Artificial magnetic conductor (AMC) ground planes and a tunable terahertz absorber generated by the HGP are compared with designs available in the literature. The HGP is shown to produce human-competitive results. The AMC ground planes synthesised by the HGP were found to produce improved results including wider bandwidths and larger reflection coefficient magnitudes than that of the human designs. For one of the designed AMCs, the HGP's bandwidth is 73.3percent larger and the minimum reflection magnitude is 1.0percent larger than the reference AMC. Similarly, the absorber synthesised by the HGP has larger bandwidths than that of a recently published absorber optimised by random hill climbing. Three bias voltages were tested with the tunable absorber. The bandwidths of the HGP absorber are 23.1percent, 37.6percent, and 400percent larger than the reference absorber, for biases of 4, 2, and 0.5 V/nm, respectively. Four example designs are discussed together with comparative results to illustrate the advantages of the developed HGP-enabled design method.",
• notes = "Also known as \cite{8276236}",

}

Genetic Programming entries for Scott Clemens Magdy F Iskander Zhengqing Yun Jennifer Taylor Rayno

Citations