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- Title
SLL Reduction in Linear Antenna Arrays by Genetic Algorithm, Flower Pollination Algorithm, and Grey Wolf Optimization with Iteration and Population Parameters.
- Authors
Asaad, Huda; Hreshee, Saad S.
- Abstract
The combination of antenna arrays with optimization algorithms aims to minimize SLL, Linear antenna arrays are an extensively used electromagnetic system in modern wireless communication. The improvement algorithms are the genetic algorithm GA, the flower pollination algorithm FPA, and the grey wolf optimization GWO. This has been implemented to reduce SLL and communicate the signal to the right place and the highest efficiency with the greatest amount of energy and by reaching the best solution. antenna arrays engineering was arranged in linearity and implemented in different numbers of elements, i.e.8,16,32,64,128, and 256 elements, Each algorithm has criteria that affect the reduction of SLL, In GA when considering the influential parameters represented by iteration, population size, and max stall iteration, the best effect is iteration where SLL is reduced to -32.9523dB and at 16-element at iteration 50. FPA has many influential parameters representing iteration, population size, probability, and flower attraction rate. The best of these effects is iteration. SLL reduced to -35.0696dB at iteration 300 and at 64-element. In GWO the influential parameters are iteration and population size the best effect, it was concluded, is iteration as well, which has reduced SLL to -32.8479dB at 8-element in iteration 140.
- Subjects
LINEAR antenna arrays; OPTIMIZATION algorithms; PARAMETERS (Statistics); ANTENNA arrays; GENETIC algorithms; ALGORITHMS; BEES algorithm
- Publication
Revue d'Intelligence Artificielle, 2023, Vol 37, Issue 5, p1177
- ISSN
0992-499X
- Publication type
Article
- DOI
10.18280/ria.370509