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Oil Price Forecasting Based on EMD and BP_AdaBoost Neural Network

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Document pages: 10 pages

Abstract: Empirical mode decomposition (EMD) and BP AdaBoost neural network areused in this paper to model the oil price. Based on the benefits of these twomethods, we predict the oil price by using them. To a certain extent, it effectivelyimproves the accuracy of short-term price forecasting. Forecast results of thismodel are compared with the results of the ARIMA model, BP neural network andEMD-BP combined model. The experimental result shows that the root mean squareerror (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE)and Theil inequality (U) of EMD and BP AdaBoost model are lower than othermodels, and the combined model has better prediction accuracy.

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