It is known that type-2 fuzzy sets let us to model and to minimize the effects of uncertainties in rule-based fuzzy logic system (FLS). While a type-2 FLS has the capability to model more complex relationships, the output ...

This paper addresses a new method for automatically extraction of the fuzzy rules from input-output data. The proposed fuzzy system modeling approach has three significant modules: (1) input selection; (2) knowledge ...

In this paper a new fuzzy modeling approach is proposed, which is devoted to discover knowledge from

data and represent it in the form of fuzzy rules. In this approach, the structure identification and parameter ...

This paper presents a similarity measure for interval type-2 fuzzy sets based on the intersection of the footprint of uncertainty. We also established the closed-form of the proposed similarity measures for Gaussian interval ...

Different similarity measures for type-2 fuzzy sets have heen proposed in the literature. However, there are not analytIcal formulas for them. In this paper, an extension of Jaccard\\'s similarity ...

In this paper, a type-2 Fuzzy Rule Based Expert System is developed for analysing the stock markets. Interval type-2 fuzzy logic system permits us to model rule uncertainties and every membership value of an element is ...

In this paper a new fuzzy modeling approach is proposed, which is devoted to discover knowledge from data and represent it in the form of fuzzy rules. In this approach, the structure identification and parameter optimization ...

One of the main advantages of interval type-2 fuzzy logic systems is their ability to produce prediction intervals as a by-product of the type reduction process. This is especially useful for the design of interval type-2 ...