Evolved-Design-Of-Microstrip-Patch-Antenna-by-Genetic-Programming - Author: thuan.bb.hust@gmail.com
Current methods of designing and optimizing antennas by hand are time, effortful, limit complexity and require significant professionalism and experience. With this approach, an antenna engineer will select specific class of antenna and then spend huge amount of time for adjusting and testing to get desired results. Also, the antennas need to be inexpensive, efficient, and robust for the installation environment. The conventional optimizers can only find the best solution among pre-defined shapes of antenna . As another approach which can overcome these limitations is building an evolutionary software that can find out the effective design solution that would originally not be found and has capable of solving the need of conformal and multiband in restricted area. Therefore, this work places emphasis on new approach which uses machine learning technique (genetic programming) to automatically design the antennas and describe an example of innovative microstrip patch antenna (MPA) created using this technology that operates at 3.5 GHz as an ideal and suggested bandwidth of 5G technology
