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Deep Investigation of Machine Learning Techniques for Optimizing the Parameters of Microstrip Antennas. |
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| รหัสดีโอไอ | |
| Creator | Abdelaziz A. Abdelhamid, Sultan R. Alotaibi |
| Title | Deep Investigation of Machine Learning Techniques for Optimizing the Parameters of Microstrip Antennas. |
| Contributor | - |
| Publisher | TuEngr Group |
| Publication Year | 2564 |
| Journal Title | International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies |
| Journal Vol. | 12 |
| Journal No. | 13 |
| Page no. | 12A13N: 1-15 |
| Keyword | Microstrip antenna, Machine learning, Regression models, Neural networks, Parameters optimization |
| URL Website | http://TuEngr.com/Vol12_13.html |
| Website title | ITJEMAST V12(13) 2021 @ TuEngr.com |
| ISSN | 2228-9860 |
| Abstract | This paper presents a deep investigation and analysis of the recent advances in optimizing the parameters of microstrip antennas based on machine learning techniques. This investigation explains the numerical and traditional methods necessary for understanding the insights in designing microstrip antennas. Contemporary machine learning techniques employed in parameters optimization are then discussed for emphasizing the various approaches used in antenna synthesis. In addition, the regression methods in machine learning are highlighted in terms of the mathematical description and implementation of parameters optimization. Various methodologies and algorithms used to produce the design parameters of microstrip antennas based on antenna specifications and desired radiation are also described in this paper. Moreover, the recent research publications that target the design and optimization of microstrip antennas using machine learning are discussed in this paper to supply readers with the essential understanding of the recent methods required for applying the presented approaches in related tasks and projects. |
