the science parks have important role in development of technology and are able to make economic growth of the countries. the purpose of this paper is the presentation of a fuzzy expert system (fis) as intelligent systems to evaluate the science and technology parks. one of the problems for evaluating science and technology parks is to have the high number of criteria and science parks which ah...

This paper reports the use of simulated annealing to design more efficient fuzzy logic systems to model problems with associated uncertainties. Simulated annealing is used within this work as a method for learning the best configurations of interval and general type-2 fuzzy logic systems to maximize their modeling ability. The combination of simulated annealing with these models is presented in...

Controller design remains an elusive and challenging problem foruncertain nonlinear dynamics. Interval type-2 fuzzy logic systems (IT2FLS) incomparison with type-1 fuzzy logic systems claim to effectively handle systemuncertainties especially in the presence of disturbances and noises, but lack aformal mechanism to guarantee performance. In contrast, adaptive sliding modecontrol (ASMC) provides...

We introduce a type-2 fuzzy logic system (FLS), which can handle rule uncertainties. The implementation of this type-2 FLS involves the operations of fuzzification, inference, and output processing. We focus on “output processing,” which consists of type reduction and defuzzification. Type-reduction methods are extended versions of type-1 defuzzification methods. Type reduction captures more in...

In this paper some algebraic structures for linguistic fuzzy models are defined for the first time. By definition linguistic fuzzy norm, stability of these systems can be considered. Two methods (normed-based & graphical-based) for stability analysis of linguist fuzzy systems will be presented. At the follow a new simple method for linguistic fuzzy numbers calculations is defined. At the end tw...

Traditional fuzzy logic systems are unable to handle the uncertainties of real-world applications. By "handle" I mean directly model and minimize the effect of. In this talk I will explain rule-based type-2 fuzzy logic systems and how they can handle a broad range of uncertainties totally within their framework. This is accomplished by adding a new mathematical dimension-a third dimension-to ty...

Recently there has been significant growth in research interest in type-2 fuzzy logic. Type-2 fuzzy logic is extension of type-1 (regular) fuzzy logic where the membership grade in a fuzzy set is itself measured as a fuzzy number. Much of this growth has only been concerned with type-2 interval fuzzy systems, a subset of type-2 fuzzy systems, where the membership grade of a fuzzy set is given a...