Images of fuzzy sets under fuzzy relations have been investigated mainly in two contexts: On the one hand, mostly under the term “full image” [5], they can be regarded as very general tools for fuzzy inference, leading to the so-called “compositional rule of inference” [1, 5]. On the other hand, under the term “extensional hull”, the image of a fuzzy set under a fuzzy equivalence relation yield...

This paper presents a new interval type-2 fuzzy inference system to handle uncertainty using reduced-set vector learning mechanism based on hybrid kernels. Firstly, a novel concept, interval kernel, is proposed. It establishes a relationship between interval type-2 fuzzy membership and hybrid kernel. According to it, a particular interval type-2 fuzzy inference system is built, which abandons t...

Recently, Coloured Petri Nets (CPNs) have been widely used for modelling asynchronous discrete events exhibited in dynamic systems, while Fuzzy Petri Nets (FPNs) used for systems that involve approximate reasoning and uncertainty knowledge inference. In this paper, we propose a net-based structure, the so-called Fuzzy Coloured Petri Nets (FCPNs) to model both the dynamic behaviour and inexact p...

Functional equivalence of radial basis function (RBF) networks and a class of fuzzy inference systems is considered. The class of fuuy systems based on the Takagi-Sugeno model is referred to as TS-model of fuzzy inference. From the abstract mathematical viewpoint the functional equivalence between radial basis function networks and fuzzy inference systems is already shown. However, from the vie...

Cancer research is one of the major research areas in the medical field. Adaptive Neuro Fuzzy Interference System is used for the classification of Cancer. This algorithm compared with proposed algorithm of Adaptive Neuro Fuzzy Interference system with Runge Kutta learning method for the best classification of cancer. It is one of the better techniques for the classification of the cancer. The ...

Finding the compromise between computational complexity and adaptation potential of linguistic fuzzy systems is important in several fields of application of fuzzy systems including fuzzy modeling and control. This paper considers the role of popular sand t-norms in fuzzy inference function in this aspect and presents some recently acquired results. First, it is shown that with simultaneous app...

The compositional rule of inference (CRI) introduced by Zadeh is widely used in approximate reasoning schemes using fuzzy sets. In this work we show that the Bandler-Kohout subproduct does possess all the important properties such as equivalent and reasonable conditions for their solvability, their interpolative properties and the preservation of the indistinguishability that may be inherent in...

This paper describes the design of Compact, accurate and inexpensive Fuzzy Logic Controllers and Fuzzy Inference Systems which estimates the attitude of Unmanned Aerial Vehicles(UAV).Attitude refers to parameters of Unmanned Aerial Vehicle such as latitude, longitude and altitude and angles of rotation known as pitch and roll. A Soft Computing technique called Fuzzy Logic is used to design the ...

Many researchers have been interested in approximation properties of fuzzy logic systems (FLS), which like neural networks can be seen as approximation schemes. Almost all of them tackled Mamdani fuzzy model, which was shown to have many interesting features. This paper aims to present alternatives for traditional inference mechanisms and CRI method. The most attractive advantage of these new m...

Data are frequently not precise numbers but more or less non-precise, also called fuzzy. Moreover a-priori information in Bayesian inference is usually not available as a precise probability distribution. In case of fuzzy data and fuzzy a-priori information Bayes' theorem has to be generalized. There are different approaches for a generalization of Bayes' theorem but most of them don't keep the...