{"title":"一种基于神经网络的电磁优化混合算法","authors":"Yanan Liu, Tianjian Lu, Ken Wu, Jianming Jin","doi":"10.1109/EPEPS.2018.8534264","DOIUrl":null,"url":null,"abstract":"We propose a hybrid algorithm for electromagnetic optimization. The algorithm combines the genetic algorithm and gradient based optimization, leveraging the power of neural networks in both. The effectiveness and efficiency of the proposed algorithm are demonstrated using antenna and microwave filter design examples.","PeriodicalId":403235,"journal":{"name":"2018 IEEE 27th Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Hybrid Algorithm for Electromagnetic Optimization Utilizing Neural Networks\",\"authors\":\"Yanan Liu, Tianjian Lu, Ken Wu, Jianming Jin\",\"doi\":\"10.1109/EPEPS.2018.8534264\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a hybrid algorithm for electromagnetic optimization. The algorithm combines the genetic algorithm and gradient based optimization, leveraging the power of neural networks in both. The effectiveness and efficiency of the proposed algorithm are demonstrated using antenna and microwave filter design examples.\",\"PeriodicalId\":403235,\"journal\":{\"name\":\"2018 IEEE 27th Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 27th Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EPEPS.2018.8534264\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 27th Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EPEPS.2018.8534264","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Hybrid Algorithm for Electromagnetic Optimization Utilizing Neural Networks
We propose a hybrid algorithm for electromagnetic optimization. The algorithm combines the genetic algorithm and gradient based optimization, leveraging the power of neural networks in both. The effectiveness and efficiency of the proposed algorithm are demonstrated using antenna and microwave filter design examples.