Application of New Combination Weight to Combination Forecasting Model
Journal Title: 河南科技大学学报（自然科学版） - Year 2018, Vol 39, Issue 2
Abstract
In order to improve the prediction accuracy, a new method to calculate the combination weights was proposed. The weight value of the combination model was determined by combining the mean absolute percentage error ( MAPE) with the least square method.The new combination weights method was applied to a combination model, and the gross domestic product ( GDP) of Hubei province was forecasted by using the combination model. Firstly, the autoregressive integrated moving average ( ARIMA) model and exponential curve regression model were established. Then MAPE and least square method were used to determine the weight coefficient of the combined model.On this basis, the two weight coefficients were combined to form the combined weight. The predication results show that the prediction accuracy of the combined model with the combined weight is improved about 0.3% compared with the single weight.
Authors and Affiliations
Pei LI, Sijun PENG
Keywords
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