{"title":"基于卷积神经网络的电磁仿真结果可信度评估","authors":"Jinjun Bai;Yulei Liu;Dewu Kong;Kaibin Guo","doi":"10.1109/LEMCPA.2022.3226151","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":100625,"journal":{"name":"IEEE Letters on Electromagnetic Compatibility Practice and Applications","volume":"5 1","pages":"16-21"},"PeriodicalIF":0.9000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Credibility Evaluation of Electromagnetic Simulation Results Based on Convolutional Neural Network\",\"authors\":\"Jinjun Bai;Yulei Liu;Dewu Kong;Kaibin Guo\",\"doi\":\"10.1109/LEMCPA.2022.3226151\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":100625,\"journal\":{\"name\":\"IEEE Letters on Electromagnetic Compatibility Practice and Applications\",\"volume\":\"5 1\",\"pages\":\"16-21\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Letters on Electromagnetic Compatibility Practice and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/9968193/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Letters on Electromagnetic Compatibility Practice and Applications","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/9968193/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Credibility Evaluation of Electromagnetic Simulation Results Based on Convolutional Neural Network
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.