AN ADAPTIVE EVOLUTIONARY ALGORITHM FOR UWB MICROSTRIP ANTENNAS OPTIMIZATION USING A MACHINE LEARNING TECHNIQUE

作者：Silva Claudio R M^*; Martins Sinara R

来源：Microwave and Optical Technology Letters, 2013, 55(8): 1864-1868.

DOI：10.1002/mop.27692

• multiobjective evolutionary algorithms
• machine learning
• genetic algorithm optimization

This article presents an application of a machine learning technique to enhance a multiobjective evolutionary algorithm to estimate fitness function behaviors from a set of experiments made in laboratory to analyze a microstrip antenna used in ultra wideband wireless devices. These function behaviors are related to three objectives: bandwidth, return loss, and central frequency deviation. Each objective is used inside an aggregate adaptive weighted fitness function that estimates the behavior in the algorithm. The machine learning technique enabled a dynamic estimation of an aggregated compound fitness function and made it possible to a prototype algorithm to learn and adapt with a set of experiments stored in a web system repository. The final results were then compared with the ones obtained with a similar antenna modeled in a simulator program and with the ones of a real prototype antenna built from the optimal values obtained after the optimization.

• 出版日期2013-8