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In order to improve the accuracy of forecasting crude oil prices, a new crude oil price forecasting method is introduced in the paper that is a combination of the FNN model and the stochastic time effective function—namely, the WT-FNN model. The FNN model keeps track of the historical values of crude oil prices and predicts future crude oil prices, and the stochastic time effective function gives greater weight to recent information and smaller weight to old information, thus making the prediction of crude oil prices more reasonable. We selected the daily data of Brent crude oil prices from 4 January 2000 to 30 September 2021 as research objects and then used the WT-FNN model to train and predict the research objects. By comparing it to the benchmark model, we found that the predictive effect of the WT-FNN model was better than the FNN model and the no-change model. The results also passed a robustness test. [ABSTRACT FROM AUTHOR]

In this paper, an improved slope-based method (ISBM) based on empirical mode decomposition (EMD) and feed-forward neural network (FNN) method, namely, the EMD-ISBM-FNN method is introduced to decompose and forecast the crude oil prices. Firstly, the ISBM-based EMD method is used to decompose the time series of Brent crude oil prices into several IMFs (intrinsic mode functions) and residuals r n (t). Then IMFs and residuals r n (t) are inputted into the FNN model as input layer neurons, which are trained and integrated by the FNN model to study the relationship between the output values of the FNN and actual values. In order to verify the forecasting results of the EMD-ISBM-FNN model, two research frameworks and three strategies are designed, and the EMD-FNN model and the FNN model as the benchmark models are constructed to compare their forecasting results. The research shows that the EMD-ISBM-FNN model proposed in this paper has the best forecasting effect under the three strategies, and the research framework of this paper is better than the previous scholars' research frameworks, too. • A novel data envelope method (ISBM) is proposed based on EMD algorithm and neural network. • The Fixed window iterative strategy created the best results in the three strategies. • A new research plan is designed by the EMD-ISBM-FNN model. [ABSTRACT FROM AUTHOR]