type fuzzy

AIP conference proceedings

We knows that the most common use of Type 2 ambiguity (T2 FS) is to treat and control the vagueness and uncertainty found in the Type 1 ambiguity group. In T2 FS, The fuzzifier m is the most important type 2 (T2 FS) parameter. Therefore, determining a constant value for interference can be done on an ongoing basis. In this paper, several methods have been studied. The first method was the aggregation of interval type 2-interval potential fuzzy C-mean (IT2PFCM) to classify a given pattern. In the second IT2 PFCM method used for aggregation, the value of the fitting fuzzification constant was calculated for each data adaptively. Then the information was extracted from each point in the data through the graph approach, then we used two constants for m1 and m2 noise using the extracted information, and those values were found and determined in this way i.e. the lowest and highest organic values for an obscure type 2 interval.

Image enhancing using both interval type-2 fuzzy sets and IT2PFCM