A Novel Composition Forecasting Model Based on Choquet Integral with Respect to L-Measure and O-Density

Abstract

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.

High Order Lambda Measure Based Choquet Integral Composition Forecasting Model

“…The well-known composition functions of forecasting model are linear [1][2][3], in our previous works, the non-linear composition forecasting model were considered by using Choquet integral with respect to some fuzzy measures [4]. For any given fuzzy density, both Zadeh's P-measure [5][6] and Sugeno's λ-measure [5][6][7] are univalent fuzzy measures with only one formulaic fuzzy measure solution, a multivalent fuzzy measure with infinite formulaic fuzzy measure solutions based on P-measure, called L-measure [6], was proposed by , but it does not contain the λ-measure and the largest fuzzy measure, B-measure [8].…”

“…In this paper, an improved multivalent fuzzy measure, called the high order λ-measure, is proposed. Based on the Choquet integral with respect to this new measure, an improved composition forecasting model is proposed as well, an experiment with a real data by using the 5 fold cross validation mean square error [2][3][4][5][6][7][8][9] will show that the performance of the proposed composition forecasting model based on Choquet integral with respect to the proposed high order λ-measure, will be better than others.…”