Abstract
In this paper, a new hybrid approach is presented to analyze factors affecting crude oil price using rough set and wavelet neural network. Related factors that affect crude oil price are found using text mining technique and Brent oil price is chosen as the decision price because it plays an important role in world crude oil markets. The relevant subsets of the factors are discovered by rough set module and the main factors are got, and then the important degrees of these are measured using wavelet neural network. Based on the novel hybrid approach, the predictability of crude oil price is discussed.
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Xu, W., Wang, J., Zhang, X., Zhang, W., Wang, S. (2007). A New Hybrid Approach for Analysis of Factors Affecting Crude Oil Price. In: Shi, Y., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds) Computational Science – ICCS 2007. ICCS 2007. Lecture Notes in Computer Science, vol 4489. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72588-6_154
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DOI: https://doi.org/10.1007/978-3-540-72588-6_154
Publisher Name: Springer, Berlin, Heidelberg
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