| Literature DB >> 18711520 |
P Y Chen1, C H Chen, H Wang, J H Tsai, W X Ni.
Abstract
In this article, we present a genetic algorithm (GA) as one branch of artificial intelligence (AI) for the optimization-design of the artificial magnetic metamaterial whose structure is automatically generated by computer through the filling element methodology. A representative design example, metamaterials with permeability of negative unity, is investigated and the optimized structures found by the GA are presented. It is also demonstrated that our approach is effective for the synthesis of functional magnetic and electric metamaterials with optimal structures. This GA-based optimization-design technique shows great versatility and applicability in the design of functional metamaterials.Entities:
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Year: 2008 PMID: 18711520 DOI: 10.1364/oe.16.012806
Source DB: PubMed Journal: Opt Express ISSN: 1094-4087 Impact factor: 3.894