OPTIMIZATION OF A DUAL RING ANTENNA BY MEANS OF ARTIFICIAL NEURAL NETWORK
| Autor: | Riccardo E. Zich, Linh Ho Manh, Marco Mussetta, Francesco Grimaccia |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Microstrip antenna
Surrogate model Artificial neural network Computer science business.industry Bandwidth (signal processing) Computer Science::Symbolic Computation Artificial intelligence Electrical and Electronic Engineering Condensed Matter Physics business Algorithm Electronic Optical and Magnetic Materials |
| Zdroj: | Progress In Electromagnetics Research B. 58:59-69 |
| ISSN: | 1937-6472 |
| DOI: | 10.2528/pierb13112806 |
| Popis: | In literature, heuristic algorithms have been successfully applied to a number of electromagnetic problems. The associated cost functions are commonly linked to full-wave analysis, leading to complexity and high computational expense. Artiflcial Neural Network is one of the most efiective biological inspired techniques. In this article, an e-cient surrogate model is trained to replace the full-wave analysis in optimizing the bandwidth of microstrip antenna. The numerical comparison between ANN substitution model and full-wave characterization shows signiflcant improvements in time convergence and computational cost. To verify the robustness of this approach, all these concepts are integrated into a case study represented by a rectangular ring antenna with proximity-coupled feed antenna. |
| Databáze: | OpenAIRE |
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