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A hybrid transfer learning model for crude oil price forecasting
Xiao, Jin1,2; Hu, Yi3; Xiao, Yi4; Xu, Lixiang2,5; Wang, Shouyang6
2017
Source PublicationSTATISTICS AND ITS INTERFACE
ISSN1938-7989
Volume10Issue:1Pages:119-130
AbstractMost of the existing models for oil price forecasting only use the data in the forecasted time series. This study proposes a hybrid transfer learning model (HTLM) for crude oil price forecasting. We first selectively transfer some related time series in the source domain to assist in modeling the target time series by using a transfer learning technique, and then construct the forecasting model using the analog complexing (AC) method. Further, we introduce a genetic algorithm to find the optimal match between two important parameters in HTLM. Finally, we use two main crude oil price time series the West Texas Intermediate (WTI) and the Brent crude oil spot prices for empirical analysis. Our results show the effectiveness and superiority of the proposed model compared with existing models.
KeywordHybrid transfer learning model Analog complexing Genetic algorithm Crude oil price forecasting Transfer learning technique
Language英语
Funding ProjectNatural Science Foundation of China[71471124] ; Natural Science Foundation of China[71301160] ; National Social Science Foundation of China[14BGL175] ; Youth Foundation of Sichuan Province[2015RZ0056] ; Excellent Youth fund of Sichuan University[skqx201607] ; MOE Youth Project of Humanities and Social Sciences[15YJC860034] ; Natural Science Foundation of Anhui Higher Education Institutions[KJ2016A604] ; Youth backbone visiting research key project[gxfxZD2016219] ; CSC[201506500007]
WOS Research AreaMathematical & Computational Biology ; Mathematics
WOS SubjectMathematical & Computational Biology ; Mathematics, Interdisciplinary Applications
WOS IDWOS:000386413100012
PublisherINT PRESS BOSTON, INC
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/23835
Collection系统科学研究所
Corresponding AuthorXiao, Yi
Affiliation1.Sichuan Univ, Sch Business, Chengdu 610064, Peoples R China
2.Univ Munster, Dept Math & Comp Sci, D-48149 Munster, Germany
3.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China
4.Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China
5.Hefei Univ, Dept Mathmat & Phys, Hefei 230601, Peoples R China
6.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Xiao, Jin,Hu, Yi,Xiao, Yi,et al. A hybrid transfer learning model for crude oil price forecasting[J]. STATISTICS AND ITS INTERFACE,2017,10(1):119-130.
APA Xiao, Jin,Hu, Yi,Xiao, Yi,Xu, Lixiang,&Wang, Shouyang.(2017).A hybrid transfer learning model for crude oil price forecasting.STATISTICS AND ITS INTERFACE,10(1),119-130.
MLA Xiao, Jin,et al."A hybrid transfer learning model for crude oil price forecasting".STATISTICS AND ITS INTERFACE 10.1(2017):119-130.
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