In this paper an adaptive neuro fuzzy inference system based on interval Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as coefficients of linear combination of input variables in the consequent part is presented. The capability of the proposed method (we named ANFIS2) to function approximation and dynamical system identification is shown. The ANFIS2 structure ...

in the present paper, we study some properties of fuzzy norm of linear operators. at first the bounded inverse theorem on fuzzy normed linear spaces is investigated. then, we prove hahn banach theorem, uniform boundedness theorem and closed graph theorem on fuzzy normed linear spaces. finally the set of all compact operators on these spaces is studied.

It seems that a suitably constructed fuzzy sets of natural numbers form the most complete and adequate description of cardinality of finite fuzzy sets.(see [11]) Nevertheless, in many applications one needs a simple scalar evaluation of that cardinality by nonnegative real number, e.g scalar cardinality. There are many approaches to this evaluation-sigma count of fuzzy set,psigma count of fuzzy...

Fuzzy clustering algorithms like the popular fuzzy cmeans algorithm (FCM) are frequently used to automatically divide up the data space into fuzzy granules (fuzzy vector quantization). In the context of fuzzy systems, in order to be intuitive and meaningful to the user, the fuzzy membership functions of the used linguistic terms have to fulfill some requirements like boundedness of support or u...

Abstract We present a new type of fuzzy controller constructed with the B spline model and its applications in modelling and control Un like the other normalised parameterised set functions for de ning fuzzy sets B spline basis functions do not necessarily span from membership value to but possess the property partition of unity These B spline basis functions are automatically determined after ...

Fuzzy set theory has entered into a large variety of disciplines of sciences,technology and humanities having established itself as an extremely versatileinterdisciplinary research area. Accordingly different notions of fuzzystructure have been developed such as fuzzy normed linear space, fuzzytopological vector space, fuzzy sequence space etc. While reviewing theliterature in fuzzy sequence sp...

In complex manufacturing, the system parameters have dynamic and nonlinear characters. Existing parameters setting methods show low efficiency and accuracy, and some setting experience accumulated in engineering practice can not be fully used. Therefore, an online parameter setting method with improved adaptive neuro-based fuzzy inference model is proposed in this paper. The advantages of ANFIS...

In this paper we present our research of online hot topic detection and label extraction method for our hot topic recommendation system. Using a new topical feature selection method, the feature space is compressed suitable for an online system. The tolerance rough set model is used to enriching the small set of topical feature words to a topical approximation space. According to the distance d...

This paper presents a novel adaptive neuro-fuzzy inference system based on interval Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as coefficients of linear combination of input variables in the consequent part. The capability of the proposed ANFIS2 for function approximation and dynamical system identification is remarkable. The structure of ANFIS2 is very sim...