[Yang, Hua] School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan, 430023, China
[Zhang, Yunfei; Jiang, Feng] School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan, 430073, China
语种：
英文
期刊：
Chinese Control Conference
ISSN：
1934-1768
年：
2019
卷：
2019-July
页码：
8944-8949
会议名称：
38th Chinese Control Conference, CCC 2019
会议时间：
July 27, 2019 - July 30, 2019
会议地点：
Guangzhou, China
会议主办单位：
(1) School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan; 430023, China; (2) School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan; 430073, China
会议赞助商：
Chinese Association of Automation (CAA);Guangdong University of Technology;Systems Engineering Society of China (SESC);Technical Committee on Control Theory (TCCT), Chinese Association of Automation (CAA)
The frequent fluctuations in international crude oil prices may affect the stability of the global economy and society. The fluctuation of crude oil prices has nonlinearity, uncertainty and volatility, which bring certain challenges for forecasting crude oil prices. In this paper we use hybrid model with the empirical mode decomposition (EMD) and Back Propagation Neural Network (BPNN) to predict the crude oil prices. To improve the accuracy of prediction, we firstly decompose the crude oil prices data into a series of independent intrinsic mode functions (IMFs) and residual sequences by the em...
