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We propose two hybrid prediction models for the international crude oil price: sarima-bp hybrid model; and ssvm model. The sarimabp hybrid model combines seasonality analysis and autoregressive integrated moving average with back propagation neural network model. The ssvm model combines seasonality analysis with support vector machines. New York Mercantile Exchange (nymex) crude oil's monthly closing price, which ranges from January 2002 to April 2016, is selected as the experimental data sets.doi:10.21914/anziamj.v58i0.10995 fatcat:b6dtajkeuff3zi4gkixn4ybi5a