A novel composition forecasting model based on choquet integral with respect to L-measure and O-density

In this paper, based on L-measure and O-density, a novel composition forecasting model is proposed. For evaluating this new composition forecasting model, a real data experiment by using the sequential mean square error was conducted. Based on O-density, the performances of Choquet integral composition forecasting model with the L-measure, Lambda-measure and P-measure, respectively, a ridge regression composition forecasting model and a multiple linear regression composition forecasting model and the traditional linear weighted composition forecasting model were compared. Experimental results show that the Choquet integral composition forecasting model with respect to the L-measure outperforms other 5 composition forecasting models.