新型进化神经网络

Wei Gao
{"title":"新型进化神经网络","authors":"Wei Gao","doi":"10.1109/ICNIC.2005.1499869","DOIUrl":null,"url":null,"abstract":"The evolutionary neural network can be generated combining the evolutionary computation and neural network. Based on analysis of merits and demerits of previously proposed evolutionary neural network models, combining the immunized evolutionary programming proposed by author and BP neural network, a new evolutionary neural network model whose architecture and connection weights evolve simultaneously is proposed. At last, through the typical XOR problem, the new model is compared and analyzed with BP neural network and traditional evolutionary neural network. The computing results show that the precision and efficiency of the new model are all good.","PeriodicalId":169717,"journal":{"name":"Proceedings. 2005 First International Conference on Neural Interface and Control, 2005.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"New evolutionary neural networks\",\"authors\":\"Wei Gao\",\"doi\":\"10.1109/ICNIC.2005.1499869\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The evolutionary neural network can be generated combining the evolutionary computation and neural network. Based on analysis of merits and demerits of previously proposed evolutionary neural network models, combining the immunized evolutionary programming proposed by author and BP neural network, a new evolutionary neural network model whose architecture and connection weights evolve simultaneously is proposed. At last, through the typical XOR problem, the new model is compared and analyzed with BP neural network and traditional evolutionary neural network. The computing results show that the precision and efficiency of the new model are all good.\",\"PeriodicalId\":169717,\"journal\":{\"name\":\"Proceedings. 2005 First International Conference on Neural Interface and Control, 2005.\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 2005 First International Conference on Neural Interface and Control, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNIC.2005.1499869\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 2005 First International Conference on Neural Interface and Control, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNIC.2005.1499869","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

摘要

将进化计算与神经网络相结合,可以生成进化神经网络。在分析前人提出的进化神经网络模型优缺点的基础上,将作者提出的免疫进化规划与BP神经网络相结合,提出了一种结构与连接权同时进化的进化神经网络模型。最后,通过典型的异或问题,将新模型与BP神经网络和传统的进化神经网络进行了比较分析。计算结果表明,新模型具有良好的精度和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New evolutionary neural networks
The evolutionary neural network can be generated combining the evolutionary computation and neural network. Based on analysis of merits and demerits of previously proposed evolutionary neural network models, combining the immunized evolutionary programming proposed by author and BP neural network, a new evolutionary neural network model whose architecture and connection weights evolve simultaneously is proposed. At last, through the typical XOR problem, the new model is compared and analyzed with BP neural network and traditional evolutionary neural network. The computing results show that the precision and efficiency of the new model are all good.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信