based on the point of view of geometrical representation of an intuitionistic fuzzy set, we take into account all three parameters describing intuitionistic fuzzy set, propose a kind of new method to calculate correlation and correlation coefficient of intuitionistic fuzzy sets which is similar to the cosine of the intersectional angle in finite sets and probability space, respectively. further...

A design methodology of interval type-2 fuzzy c-means clustering algorithm-based fuzzy inference systems (IT2FCMFIS) is introduced in this paper. An interval type-2 fuzzy c-means (IT2FCM) clustering algorithm is developed to generate the fuzzy rules in the form of the scatter partition of input space. And the individual partitioned spaces describe the fuzzy rules equal to the number of clusters...

An interval type-2 fuzzy set (IT2FS) contains the infinite number of embedded membership functions (MFs) defined as type-1 sets. The center gravity (COG) an IT2FS is obtained by integrating centroids all these MFs. However, obtaining COG in a continuous domain impossible because MFs and, discrete domain, comes with exponential time complexity. Therefore, different algorithms were proposed to fi...

Neural Networks (NN), Type-1 Fuzzy Logic Systems (T1FLS) and Interval Type-2 Fuzzy Logic Systems (IT2FLS) are universal approximators, they can approximate any non-linear function. Recent research shows that embedding T1FLS on an NN or embedding IT2FLS on an NN can be very effective for a wide number of non-linear complex systems, especially when handling imperfect information. In this paper we...

Type-2 fuzzy sets were introduced by Zadeh in 1975 in a series of papers. The basic idea is to generalize the notion of ordinary fuzzy sets (type-1), a¤ording wider applicability. This paper gives a general overview of some of the mathematical aspects of type-2 fuzzy set theory, emphasizing precisely how type-2 generalizes type-1 and interval-valued fuzzy set theory. We will summarize the theor...

In this paper, an adaptive H interval type-2 fuzzy controller is proposed for a class of unknown nonlinear discrete-time systems with training data corrupted by noise or rule uncertainties involving external disturbances. Adaptive interval type-2 fuzzy control scheme and H control approach are incorporated to implement the main objective of controlling the plant to track a reference trajectory....

In this paper, an adaptive H interval type-2 fuzzy controller is proposed for a class of unknown nonlinear discrete-time systems with training data corrupted by noise or rule uncertainties involving external disturbances. Adaptive interval type-2 fuzzy control scheme and H control approach are incorporated to implement the main objective of controlling the plant to track a reference trajectory....

a new approach to define the similarity measure betweeninterval-valued fuzzy sets is presented. the proposed approach isbased on a weighted measure in which the normalized similaritiesbetween lower functions and also between upper functions arecombined by a weight parameter. the properties of this similaritymeasure are investigated. it is shown that, the proposed measurehas some advantages in c...