학술논문

Hybrid Method of Artificial Neural Network and Simulated Annealing Algorithm for Optimizing Wideband Patch Antennas
Document Type
Periodical
Source
IEEE Transactions on Antennas and Propagation IEEE Trans. Antennas Propagat. Antennas and Propagation, IEEE Transactions on. 72(1):944-949 Jan, 2024
Subject
Fields, Waves and Electromagnetics
Aerospace
Transportation
Components, Circuits, Devices and Systems
Antennas
Patch antennas
Neurons
Wideband
Training
Testing
Bandwidth
Artificial neural network (ANN)
simulated annealing (SA) algorithm
wideband antenna
Language
ISSN
0018-926X
1558-2221
Abstract
In order to design the wideband patch antenna, a hybrid method based on the artificial neural network (ANN) and the simulated annealing (SA) algorithm is proposed in this communication. The ANN is employed to describe the nonlinear relationship between the geometric parameters and the $S$ -parameters of the antenna. The ANN is trained by the dataset obtained from the high-frequency structure simulator (HFSS). More importantly, the dataset is divided into three groups according to their own characteristics so that the ANN can be trained faster and better. The SA is employed to broaden the bandwidth of the patch antenna with the required center frequency. Then three wideband patch antennas with different center frequencies are designed to demonstrate the feasibility of the proposed method. Several slots are added to the patch to achieve the wide bandwidth. The results prove that the proposed method can obtain the wideband patch antenna quickly and efficiently.