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Applying Neural Networks to Prices Prediction of Crude Oil Futures
Joint Authors
Hu, Yi-Chung
Hu, John Wei-Shan
Lin, Ricky Ray-Wen
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-08-06
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The global economy experienced turbulent uneasiness for the past five years owing to large increases in oil prices and terrorist’s attacks.
While accurate prediction of oil price is important but extremely difficult, this study attempts to accurately forecast prices of crude oil futures by adopting three popular neural networks methods including the multilayer perceptron, the Elman recurrent neural network (ERNN), and recurrent fuzzy neural network (RFNN).
Experimental results indicate that the use of neural networks to forecast the crude oil futures prices is appropriate and consistent learning is achieved by employing different training times.
Our results further demonstrate that, in most situations, learning performance can be improved by increasing the training time.
Moreover, the RFNN has the best predictive power and the MLP has the worst one among the three underlying neural networks.
This finding shows that, under ERNNs and RFNNs, the predictive power improves when increasing the training time.
The exceptional case involved BPNs, suggesting that the predictive power improves when reducing the training time.
To sum up, we conclude that the RFNN outperformed the other two neural networks in forecasting crude oil futures prices.
American Psychological Association (APA)
Hu, John Wei-Shan& Hu, Yi-Chung& Lin, Ricky Ray-Wen. 2012. Applying Neural Networks to Prices Prediction of Crude Oil Futures. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-1029871
Modern Language Association (MLA)
Hu, John Wei-Shan…[et al.]. Applying Neural Networks to Prices Prediction of Crude Oil Futures. Mathematical Problems in Engineering No. 2012 (2012), pp.1-12.
https://search.emarefa.net/detail/BIM-1029871
American Medical Association (AMA)
Hu, John Wei-Shan& Hu, Yi-Chung& Lin, Ricky Ray-Wen. Applying Neural Networks to Prices Prediction of Crude Oil Futures. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-1029871
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1029871