“…Recently, the combination of different intelligent systems with traditional computational approaches has been proposed in different fields of research in order to develop more efficient tools [10] , [11] , [12] , [13] . In the context of computational modeling of experimental data, type-2 fuzzy systems have attracted considerable attention by researches due to its interpretable rule-based structure with capability to treat nonlinearity and uncertainty [14] , [15] , [16] .…”