Credibility Evaluation of Electromagnetic Simulation Results Based on Convolutional Neural Network

被引:2
|
作者
Bai, Jinjun [1 ]
Liu, Yulei [1 ]
Kong, Dewu [1 ]
Guo, Kaibin [1 ]
机构
[1] Dalian Maritime Univ, Coll Marine Elect Engn, Dalian 116026, Peoples R China
来源
IEEE LETTERS ON ELECTROMAGNETIC COMPATIBILITY PRACTICE AND APPLICATIONS | 2023年 / 5卷 / 01期
关键词
Electromagnetics; Training; Computational modeling; Convolutional neural networks; Standards; Simulation; Labeling; Artificial intelligence; convolutional neural network (CNN); credibility evaluation; electromagnetic simulation; feature selective validation; SELECTIVE VALIDATION FSV; CEM;
D O I
10.1109/LEMCPA.2022.3226151
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The core idea of the credibility evaluation method of electromagnetic simulation results is to replace the experts with an electromagnetic computing professional background to evaluate the credibility of simulation results. The representative algorithm is the feature selective validation (FSV) method proposed by the IEEE Standards Association. However, the existing credibility assessment methods all use statistical indicators or signal processing methods to simulate the real thoughts of experts and have not achieved true artificial intelligence. In this letter, a credibility evaluation method of simulation results based on a convolutional neural network is proposed, which aims to integrate the real ideas of experts (background knowledge of electromagnetic calculation) into the evaluation, instead of just mechanical numerical calculation, and to avoid evaluation errors caused by nonprofessional.
引用
收藏
页码:16 / 21
页数:6
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