A multi-granularity heterogeneous combination approach to crude oil price forecasting

doi:10.1016/j.eneco.2020.104790

CSpace

	A multi-granularity heterogeneous combination approach to crude oil price forecasting
	Wang, Jue 1,2; Zhou, Hao 1,2; Hong, Tao 3; Li, Xiang 1,2; Wang, Shouyang 1,2
	2020-09-01
发表期刊	ENERGY ECONOMICS
ISSN	0140-9883
卷号	91 页码:9
摘要	Crude oil price forecasting has attracted much attention due to its significance on commodities market as well as nonlinear complexity in prediction task. Combining forecasts in different granular spaces, we propose a multi-granularity heterogeneous combination approach to enhance forecasting accuracy in the study. Firstly, we introduce various feature selection techniques including filter, wrapper and embedded methods, to identify key factors that affect crude oil price and construct different granular spaces. Secondly, distinct feature subsets distinguished by different feature selection methods are incorporated to generate individual forecasts using three popular forecasting models including Linear regression (LR), Artificial neural network (ANN) and Support vector machine (SVR). Finally, the final forecasts are obtained by combining the forecasts from individual forecasting model in each granular space and the optimal weighting vector is achieved by artificial bee colony (ABC) techniques. The experimental results demonstrate that the proposed multi-granularity heterogeneous combination approach based on ABC can outperform not only individual competitive benchmarks but also single-granularity heterogeneous and multi-granularity homogenous approaches. (C) 2020 Elsevier B.V. All rights reserved.
关键词	Crude oil Price Forecast combination Feature selection Multi-granularity Artificial bee colony
DOI	10.1016/j.eneco.2020.104790
收录类别	SCI
语种	英语
资助项目	National Center for Mathematics and Interdisciplinary Sciences (NCMIS) ; Chinese Academy of Sciences (CAS) ; National Natural Science Foundation of China (NSFC)[71771208] ; National Natural Science Foundation of China (NSFC)[71271202]
WOS研究方向	Business & Economics
WOS类目	Economics
WOS记录号	WOS:000582639700002
出版者	ELSEVIER
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/52437
专题	中国科学院数学与系统科学研究院
通讯作者	Hong, Tao
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, MADIS, CEFS, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100190, Peoples R China 3.Univ North Carolina Charlotte, Syst Engn & Engn Management Dept, Charlotte, NC 28223 USA
推荐引用方式 GB/T 7714	Wang, Jue,Zhou, Hao,Hong, Tao,et al. A multi-granularity heterogeneous combination approach to crude oil price forecasting[J]. ENERGY ECONOMICS,2020,91:9.
APA	Wang, Jue,Zhou, Hao,Hong, Tao,Li, Xiang,&Wang, Shouyang.(2020).A multi-granularity heterogeneous combination approach to crude oil price forecasting.ENERGY ECONOMICS,91,9.
MLA	Wang, Jue,et al."A multi-granularity heterogeneous combination approach to crude oil price forecasting".ENERGY ECONOMICS 91(2020):9.