神经网络非线性预测器

A. Ukrainec, S. Haykin, J. McGregor
{"title":"神经网络非线性预测器","authors":"A. Ukrainec, S. Haykin, J. McGregor","doi":"10.1109/IJCNN.1989.118507","DOIUrl":null,"url":null,"abstract":"Summary form only given, as follows. The authors demonstrate that a backpropagation neural network can be used for nonlinear time series prediction. In a computer experiment an example nonlinear time series is used to teach a network the necessary mapping in a supervised manner. Predictor learning curves are presented, showing successful operation. Improvements to the neural network structure with regard to the reduction of the observed performance deficit are discussed.<<ETX>>","PeriodicalId":199877,"journal":{"name":"International 1989 Joint Conference on Neural Networks","volume":"39 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A neural network nonlinear predictor\",\"authors\":\"A. Ukrainec, S. Haykin, J. McGregor\",\"doi\":\"10.1109/IJCNN.1989.118507\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary form only given, as follows. The authors demonstrate that a backpropagation neural network can be used for nonlinear time series prediction. In a computer experiment an example nonlinear time series is used to teach a network the necessary mapping in a supervised manner. Predictor learning curves are presented, showing successful operation. Improvements to the neural network structure with regard to the reduction of the observed performance deficit are discussed.<<ETX>>\",\"PeriodicalId\":199877,\"journal\":{\"name\":\"International 1989 Joint Conference on Neural Networks\",\"volume\":\"39 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International 1989 Joint Conference on Neural Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.1989.118507\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International 1989 Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.1989.118507","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

仅给出摘要形式,如下。证明了反向传播神经网络可以用于非线性时间序列预测。在一个计算机实验中,用一个非线性时间序列的例子,以监督的方式教会一个网络必要的映射。给出了预测器的学习曲线,表明操作成功。讨论了对神经网络结构的改进,以减少观察到的性能缺陷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A neural network nonlinear predictor
Summary form only given, as follows. The authors demonstrate that a backpropagation neural network can be used for nonlinear time series prediction. In a computer experiment an example nonlinear time series is used to teach a network the necessary mapping in a supervised manner. Predictor learning curves are presented, showing successful operation. Improvements to the neural network structure with regard to the reduction of the observed performance deficit are discussed.<>
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