An Improved Choquet Integral Composition Forecasting Model Based on H-measure and O-density

Abstract

In this paper, based on H-measure and O-density, a novel Choquet integral composition forecasting model is proposed. For evaluating this improved composition forecasting model, an experiment with a real data by using the 5 fold cross validation mean square error is conducted. The performances of Choquet integral composition forecasting model with the H-measure, extensional L-measure, L-measure, Lambda-measure and P-measure, respectively, based on O-density and N-density 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. The experimental results showed that the Choquet integral composition forecasting model with respect to the H-measure and O-density outperforms others.