电波科学学报2026，Vol.41Issue(1)：117-123,7.DOI:10.12265/j.cjors.2025182
基于DeepONet的高自由度频率选择表面代理模型
DeepONet surrogate modeling of high-DOF frequency selective surfaces
摘要
Abstract
To address the challenges of low modeling efficiency and high simulation cost of frequency selective surfaces(FSS)under high-degree of freedom(high-DF)parameter spaces and complex topologies,this study proposes an artificial intelligence-based electromagnetic forward modeling approach.A neural network architecture based on deep operator network(DeepONet)is constructed,where the branch network incorporates an improved ResNet-18 to effectively extract multi-scale spatial features from FSS topology images,while the trunk network takes frequency as an explicit input to enhance the modeling capability of frequency responses.By learning the nonlinear mapping between topology and frequency response,the model achieves efficient prediction of the S21 parameter across the 2–20 GHz frequency band.The proposed framework adopts an offline training and online testing strategy,enabling the model to rapidly generate full-band responses from a single structural input,thereby significantly improving inference efficiency.Experimental results show that the average relative error of the model on the validation set is 0.047 8,the coefficient of determination(R2)is 0.994 41,and the average prediction time per sample is 6 ms.Compared with traditional finite element method(FEM)and finite-difference time-domain(FDTD)approaches,the proposed AI-based model eliminates the need for repeated meshing and re-modeling,substantially reducing computational cost.It provides a feasible and efficient path for rapid modeling and intelligent computation of complex electromagnetic structures such as FSS.关键词
频率选择表面(FSS)/人工智能/深度神经网络/正向代理模型/卷积神经网络/深度算子网络(DeepONet)Key words
frequency selective surface(FSS)/artificial intelligence/deep neural network/forward model/convolutional neural networks/deep operator network(DeepONet)分类
信息技术与安全科学引用本文复制引用
王铭恺,魏准..基于DeepONet的高自由度频率选择表面代理模型[J].电波科学学报,2026,41(1):117-123,7.基金项目
国家自然科学基金(62371417)National Natural Science Foundation of China(62371417) （62371417）
