Abstract
In this paper, we first define "advanced partitions type fuzzy integral(Definition 4)"by extending the range of partitions. Since this functional utilizes partitions only for the choice of interaction terms, it expresses more intermediate multilinear fuzzy integrals. Moreover, we develop a new modeling algorithm such that the choice of interaction terms is not dependent on statistical criteria, such as Akaike's Information criterion(AIC)and tests, aiming at making the expression of interactions by partitions applicable to the general statistical model(e.g.orthogonal polynomials). Through a concrete evaluation problem, we compare interaction terms by AIC with those by the tests based on the analysis of variance and analyze the cause of difference between them. As a result, we add the necessary procedure to the modeling algorithm(Fig.2)based on AIC.
