Pareto genetic algorithm optimization of broadband dipole antenna elements for use in a low frequency radio telescope array including mutual coupling effects

2008 ◽  
Author(s):  
A. Kerkhoff ◽  
Hao Ling
Keyword(s):  
Genetic Algorithm ◽  
Radio Telescope ◽  
Mutual Coupling ◽  
Low Frequency ◽  
Dipole Antenna ◽  
Algorithm Optimization ◽  
Coupling Effects ◽  
Genetic Algorithm Optimization ◽  
Telescope Array

Optimal parametric design of delayless subband active noise control system based on genetic algorithm optimization

2021 ◽  
pp. 107754632110016
Author(s):  
Guo Long ◽  
Yawen Wang ◽  
Teik C Lim
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Noise Control ◽  
Parametric Design ◽  
Active Noise Control ◽  
Low Frequency ◽  
Broadband Noise ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Active Noise

Active noise control systems are generally application-specific, and an appropriate algorithm with an optimal configuration is desirable in the first stage of active noise control system design and deployment. This study presents a design of the subband active noise control system with optimal parameters for a practical broadband active noise control. Although the delayless subband active noise control has gained wide attention for broadband noise cancellation, an optimal design remains a challenge because of the complex interplay between multiple factors such as spectral leakage, delay and weight stacking distortion subject to a number of configurable parameters, and weight stacking method. The configurable parameters can hardly be optimized independently because the active noise control performance depends on the combined configuration. A simple near black box active noise control algorithm optimization model is thus established by incorporating the genetic algorithm optimization into the parametric design of the delayless subband algorithm. The automated process does not require an understanding of the performance characteristics for different parameters. The significance of applying the automated genetic algorithm optimization to the complex multiparameter nonlinear active noise control design is revealed by numerical simulations, particularly for the multichannel low-frequency broadband active noise control system configured with the delayless subband algorithms. This provides a way for the optimal parametric design of subband active noise control before being used in a practical complex scenario.

GIS-based genetic algorithm optimization tool for supporting land use and land management restructuring

2007 ◽  
Vol 13 (1s) ◽  
pp. 33-37
Author(s):  
V. Makarenko ◽  
◽  
G. Ruecker ◽  
R. Sommer ◽  
N. Djanibekov ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Land Use ◽  
Land Management ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization

Genetic algorithm optimization for storing arbitrary multimode transverse images in thermal atomic vapor

2021 ◽  
Vol 118 (23) ◽  
pp. 234001
Author(s):  
Yun Chen ◽  
Chengyuan Wang ◽  
Ya Yu ◽  
Zibin Jiang ◽  
Jinwen Wang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Atomic Vapor ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization
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