Hybrid Method of Artificial Neural Network and Simulated Annealing Algorithm for Optimizing Wideband Patch Antennas

宽带 计算机科学 模拟退火 人工神经网络 算法 微带天线 电子工程 天线(收音机) 电信 人工智能 工程类
作者
Yejun He,Jinhua Huang,Wenting Li,Long Zhang,Sai‐Wai Wong,Zhi Ning Chen
出处
期刊:IEEE Transactions on Antennas and Propagation [IEEE Antennas & Propagation Society]
卷期号:72 (1): 944-949 被引量:5
标识
DOI:10.1109/tap.2023.3331249
摘要

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.
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