Fuzzy relations are able to model vagueness, in the sense that they provide the degree to which two objects are related to each other. However, they cannot model uncertainty: there is no means to attribute reliability information to the membership degrees. Intuitionistic fuzzy sets, as de1ned by Atanassov (Instuitionistic Fuzzy Sets, Physica-Verlag, Heidelberg, New York, 1999), give us a way to...

this study proposes a combination of a fuzzy sliding mode controller (fsmc) with integral-proportion-derivative switching surface based superconducting magnetic energy storage (smes) and pid tuned by a multi-objective optimization algorithm to solve the load frequency control in power systems. the goal of design is to improve the dynamic response of power systems after load demand changes. in t...

in this paper, we consider the production possibility set with n production units such that the following four principles that governs: inclusion observations, conceivability, immensity and convexity. our goal is to estimate the output of a same and new production unit with existing production possibility and amount of input is specified. so, initially we find the interval changes of each input...

In this paper, we consider moment properties for a class of quadratic adaptive fuzzy numbers defined in Dubois and Prade [D. Dubois, H. Prade, Fuzzy Sets and Systems: Theory and Applications, Academic Press, New York, 1980]. The corresponding moments of Trapezoidal Fuzzy Numbers (Tr.F.N’s) and Triangular Fuzzy Numbers (T.F.N’s) turn out to be special cases of the adaptive fuzzy number [S. Bodja...

Abstract In this paper, a fuzzy PID with new structure is proposed to solve the load frequency control in interconnected power systems. in this study, a new structure and effective of the fuzzy PID-type Load frequency control (LFC) is proposed to solve the load frequency control in interconnected power systems. The main objective is to eliminate the deviations in the frequency of different area...

We discuss the role of fuzzy sets in modeling business rules. The technology involved in fuzzy systems modeling is described. We next introduce some ideas from the Dempster-Shafer theory of evidence. We use the Dempster-Shafer framework to provide a machinery for including randomness in the fuzzy systems

Fuzziness (entropy) is a commonly used measure of uncertainty for type-1 fuzzy sets. For interval type-2 fuzzy sets (IT2 FSs), centroid, cardinality, fuzziness, variance and skewness are all measures of uncertainties. The centroid of an IT2 FS has been defined by Karnik and Mendel. In this paper, the other four concepts are defined. All definitions use a Representation Theorem for IT2 FSs. Form...

Welcome to the Journal of Intelligent and Fuzzy Systems’s special issue for “FUZZYSS’2011: 2nd International Fuzzy Systems Symposium”. Since its introduction by Prof. Dr. Lotfi A. Zadeh fuzzy logic, fuzzy sets and systems have been applied to various problems in many diverse areas. As everything try to evolve towards better states, the fuzzy theory and its applications are also evolving to mode...