Table 1: A summary of selected studies in data and feature reduction in fuzzy modeling.

ReferenceFeature reduction techniqueDataset, fuzzy model and dataOriginal data used in modelingNumber of selected featuresNumber of resulting rules
Number of instancesNumber of features

Gaweda et al. [15]The use of sensitivity analysis
Determination of essential features
Box-Jenkins gas furnace2961032

Hadjili and Wertz [16]Deviation criterion (DC): to measure the change in fuzzy partition. Removal of features that do not significantly change the fuzzy partitionNonlinear systems in noisy environment250314
Nonlinear dynamical system excited by a sinusoidal signal8001068
Run-out cooling table in a hot strip mill100017512

Zarandi et al. [18]Heuristic method to select featuresNonlinear System used in [3]50424
Supplier chance management dataset300955

Du and Zhang
[19]
Evolutionary optimizationBox-Jenkins gas furnace2961034
MR damper identification500011610

Ghazavi and Liao [20](1) Mutual
correlation methods,
(2) gene selection criteria
(3) the relief algorithm
Wisconsin breast cancer
PIMA Indian diabetes
Welding flaw identification
569
768
399
30
8
25
3
3
3
250 (3)
125 (3)

Zhang et al. [21]Iterative search margin based algorithm (Simba)Wisconsin breast cancer699953
Wine1781345
Iris150433
Ionosphere35134104