In recent years, many nearest neighbor algorithms based on fuzzy sets theory have been developed. These methods form a field, known as fuzzy nearest neighbor classification, which is the source of many proposals for the enhancement of the k nearest neighbor classifier. Fuzzy sets theory and several extensions, including fuzzy rough sets, intuitionistic fuzzy sets, type-2 fuzzy sets and possibil...

seismic hazard assessment like many other issues in seismology is a complicated problem, which is due to variety of parameters affecting the occurrence of earthquake. uncertainty, which is a result of vagueness and incompleteness of the data, should be considered in a rationale way. herein, fuzzy set theory is used to take into account the uncertainty existed in the seismic hazard analysis. the...

image segmentation is an essential issue in image description and classification. currently, in many real applications, segmentation is still mainly manual or strongly supervised by a human expert, which makes it irreproducible and deteriorating. moreover, there are many uncertainties and vagueness in images, which crisp clustering and even type-1 fuzzy clustering could not handle. hence, type-...

This contribution presents a comprehensive view on problems of approximate reasoning with imprecise knowledge in the form of a collection of fuzzy IF-THEN rules formalized by approximating formulas of a special type. Two alternatives that follow from the dual character of approximating formulas are developed in parallel. The link to the theory of fuzzy control systems is also explained.

In this paper we propose a parallel structure of I-P-D (Integral minus Proportional minus Derivative) type fuzzy controller based on the conventional PID control theory, used to control the speed of DC motor. The conventional PID controller exhibit poor performance when applied to DC motor, it fails to perform satisfactory under parameter variation or load changes. The parallel I-P-D type fuzzy...

Abstract: This paper presents a fuzzy robust controller for the nonlinear systems with uncertain dynamics. The main idea of this method is that Type-2 fuzzy system estimates nonlinear and uncertain functions exist in the system equations and then the parameters of type-2 fuzzy system are tuned online by adaptive rules obtained from Lyapunov theory and finally, stability and convergence analysis...

To make the analysis more consistent and logical according to real life situations, in thispaper, the concept of trapezoidal vague set is extended by the idea of trapezoidal vaguesets of type-II. Also we have introduced: definition of trapezoidal vague set of type-IIand arithmetic operations between two trapezoidal vague sets of type-II. Further, a newmethod has been developed f...

fuzzy linear programming problem occur in many elds such as mathematical modeling, control theory and management sciences, etc. in this paper we focus on a kind of linear programming with fuzzy numbers and variables namely fully fuzzy linear programming (fflp) problem, in which the constraints are in inequality forms. then a new method is proposed to ne the fuzzy solution for solving (fflp). ...

The standard reference in uncertainty modelling is the “Guide to the Expression of Uncertainty in Measurement (GUM)”. GUM groups the occurring uncertain quantities into “Type A” and “Type B”. Uncertainties of “Type A” are determined with the classical statistical methods, while “Type B” is subject to other uncertainties like experience with and knowledge about an instrument. Both types of uncer...