A Hybrid Approach for Antenna Optimization Using Cat Swarm based Genetic Optimization
The aim of the paper is to introduce the hybrid technique for the multiobjective optimization of antennas. The goal of the antenna optimization is typically minimising the reflection coefficient through a frequency band. To minimize the energy consumption is essential consideration of energy efficie...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Advanced Electromagnetics
2018-08-01
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| Series: | Advanced Electromagnetics |
| Subjects: | |
| Online Access: | https://aemjournal.org/index.php/AEM/article/view/624 |
| Summary: | The aim of the paper is to introduce the hybrid technique for the multiobjective optimization of antennas. The goal of the antenna optimization is typically minimising the reflection coefficient through a frequency band. To minimize the energy consumption is essential consideration of energy efficient transmission schemes that is used for the data transfer in wireless sensor networks. In our proposed work the efficient and low-cost multi objective technique CSGO (Cat Swarm based Genetic optimization) approach was used. The Cat Swarm Optimization approach is combined with genetic algorithm (GA) to optimize the bandwidth and return loss of the antenna. CSGO approach is to improve the Optimization efficiency and computational .This hybrid optimization approach will reduce the side lobe level and provide improvement in the Directivity. CSGO applied to the design of a miniaturized multiband antenna, showing better diversity and significant savings of overall optimization cost compared with the previously reported design methods. |
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| ISSN: | 2119-0275 |