变形监测数据的RBF神经网络预测方法

Guo-hui Wang, Ma Li, Hai-tao Chen
{"title":"变形监测数据的RBF神经网络预测方法","authors":"Guo-hui Wang, Ma Li, Hai-tao Chen","doi":"10.1109/MACE.2010.5536200","DOIUrl":null,"url":null,"abstract":"In order to improve the precision and reliability of prediction of deformation monitoring data, radial basis function artificial neural network is used in deformation monitoring data processing. The prediction result of this method is compared with the prediction result of BP neural network prediction methods, and it is concluded that through the radial basis function artificial neural network better prediction result can be obtained.","PeriodicalId":6349,"journal":{"name":"2010 International Conference on Mechanic Automation and Control Engineering","volume":"23 1","pages":"4874-4876"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"RBF neural network prediction method of deformation monitoring data\",\"authors\":\"Guo-hui Wang, Ma Li, Hai-tao Chen\",\"doi\":\"10.1109/MACE.2010.5536200\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to improve the precision and reliability of prediction of deformation monitoring data, radial basis function artificial neural network is used in deformation monitoring data processing. The prediction result of this method is compared with the prediction result of BP neural network prediction methods, and it is concluded that through the radial basis function artificial neural network better prediction result can be obtained.\",\"PeriodicalId\":6349,\"journal\":{\"name\":\"2010 International Conference on Mechanic Automation and Control Engineering\",\"volume\":\"23 1\",\"pages\":\"4874-4876\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Mechanic Automation and Control Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MACE.2010.5536200\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Mechanic Automation and Control Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MACE.2010.5536200","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

为了提高变形监测数据预测的精度和可靠性,将径向基函数人工神经网络应用于变形监测数据处理。将该方法的预测结果与BP神经网络预测方法的预测结果进行了比较,得出通过径向基函数人工神经网络可以获得更好的预测结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RBF neural network prediction method of deformation monitoring data
In order to improve the precision and reliability of prediction of deformation monitoring data, radial basis function artificial neural network is used in deformation monitoring data processing. The prediction result of this method is compared with the prediction result of BP neural network prediction methods, and it is concluded that through the radial basis function artificial neural network better prediction result can be obtained.
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