Time series regression and prediction based on boosting regression

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE Workshop on Advanced Research and Technology in Industry Applications, WARTIA 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages251-254
Number of pages4
ISBN (Electronic)9781479969890
DOIs
StatePublished - 4 Dec 2014
Event2014 IEEE Workshop on Advanced Research and Technology in Industry Applications, WARTIA 2014 - Ottawa, Canada
Duration: 29 Sep 201430 Sep 2014

Publication series

NameProceedings - 2014 IEEE Workshop on Advanced Research and Technology in Industry Applications, WARTIA 2014

Conference

Conference2014 IEEE Workshop on Advanced Research and Technology in Industry Applications, WARTIA 2014
Country/TerritoryCanada
CityOttawa
Period29/09/1430/09/14

Keywords

  • BP neural network
  • Boosting regression
  • Support vector machines
  • Time series

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