Time series regression and prediction based on boosting regression

Wencheng Gu, Baifeng Li, Baolong Niu, Wei Wei, Zhiming Zheng
{"title":"Time series regression and prediction based on boosting regression","authors":"Wencheng Gu, Baifeng Li, Baolong Niu, Wei Wei, Zhiming Zheng","doi":"10.1109/WARTIA.2014.6976244","DOIUrl":null,"url":null,"abstract":"In this paper we propose a boosting regression model for time series using BP network and SVR as basic learning methods. We first make brief introduction on BP network and SVR, then give the specific boosting regression algorithm with theoretical analysis. In the experiment, we use a time series data of wind-speed from a coal mine as a training set to verify the efficiency of our proposed method. The experiment results show that boosting regression gain better performance on test training and generaliz ation.","PeriodicalId":288854,"journal":{"name":"2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WARTIA.2014.6976244","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In this paper we propose a boosting regression model for time series using BP network and SVR as basic learning methods. We first make brief introduction on BP network and SVR, then give the specific boosting regression algorithm with theoretical analysis. In the experiment, we use a time series data of wind-speed from a coal mine as a training set to verify the efficiency of our proposed method. The experiment results show that boosting regression gain better performance on test training and generaliz ation.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于增强回归的时间序列回归与预测
本文提出了一种以BP网络和支持向量回归作为基本学习方法的时间序列增强回归模型。本文首先对BP网络和支持向量回归进行了简要介绍,然后给出了具体的增强回归算法,并进行了理论分析。在实验中,我们使用一个煤矿风速的时间序列数据作为训练集来验证我们提出的方法的有效性。实验结果表明,增强回归在测试训练和泛化方面取得了较好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Hospital digital library based on cloud computing Design and actualization of management system in sports teaching A topology control algorithm for ribbon wireless sensor network From the user experience to optimization design in App development process Research on communication network architecture of energy internet based on SDN
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1