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. © Springer-Verlag Berlin Heidelberg 2007.
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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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4489 LNCS, pp. 964–971). Springer Verlag. https://doi.org/10.1007/978-3-540-72588-6_154
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