DocumentCode :
176461
Title :
Time series regression and prediction based on boosting regression
Author :
Wen Gu ; Baifeng Li ; Baolong Niu ; Wei Wei ; Zhiming Zheng
Author_Institution :
Sch. of Math. & Syst. Sci., Beihang Univ., Beijing, China
fYear :
2014
fDate :
29-30 Sept. 2014
Firstpage :
251
Lastpage :
254
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.
Keywords :
backpropagation; learning (artificial intelligence); regression analysis; support vector machines; time series; BP network; SVR; basic learning method; boosting regression model; coal mine; time series regression; Biological neural networks; Boosting; Kernel; Support vector machines; Time series analysis; Training; BP neural network; boosting regression; support vector machines; time series;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Research and Technology in Industry Applications (WARTIA), 2014 IEEE Workshop on
Conference_Location :
Ottawa, ON
Type :
conf
DOI :
10.1109/WARTIA.2014.6976244
Filename :
6976244
Link To Document :
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