Accurate S parameter prediction of L‐shaped probe‐fed patch antenna with an improved artificial bee colony algorithm based on artificial neural network

• Published in: International journal of RF and microwave computer-aided engineering Vol. 31; no. 9
• Main Authors: Sun, Jianfeng, Hu, Yan, Fang, Haoyu, Wang, Zhuopeng
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.09.2021
• Subjects: Algorithms; Antenna design; Artificial neural networks; Data processing; Design optimization; improved artificial bee colony algorithm; Local optimization; L‐shaped patch antenna; Mathematical models; Microstrip antennas; Neural networks; Parameters; Patch antennas; performance prediction; S parameters; Search algorithms; Swarm intelligence
• ISSN: 1096-4290; 1099-047X
• DOI: 10.1002/mmce.22783

The determination of antenna geometric parameters is a major difficulty in the process of antenna design. With the progress of communication technology, the requirements of antenna performance are gradually improved, the design process of antenna becomes more complex to meet the performance requirements of engineering. As a mathematical model with strong information and data processing ability, artificial neural network (ANN) has been gradually applied to antenna parameters prediction and other related fields. In order to quickly and accurately obtain the model of high‐performance L‐shaped probe‐fed patch antenna, an improved artificial bee colony (IABC) algorithm was proposed. The algorithm was improved to overcome the weak local optimization ability of standard artificial bee colony (ABC) algorithm. It can be seen from the experimental results that the IABC algorithm based on ANN is an effective optimization algorithm for microstrip antenna design optimization.