| A formalism for coding fuzzy models of dynam-ical systems is presented. It is shown that the formalism is rich enough to capture the performance of arbitrary conventional discrete time dynamical systems, whose transition maps are polynomials with rational coeecients. The proof of this fact provides a constructive algorithm for generating fuzzy models to approximate an arbitrary map on a compa...

Web Information Retrieval based on Fuzzy set derives user information need from vague and imprecise user queries and therefore uses fuzzy queries to retrieve documents relevant to user’s information need. Optimization techniques have been applied successfully in various domains and results proved effective therefore a novel approach is recommended using hybrid of Ant Colony Optimization(ACO)Gen...

In this paper we describe a fuzzy Description Logic reasoner which implements resolution in order to provide reasoning services for expressive fuzzy DLs. The main innovation of this implementation is the ability to reason over assertions with abstract (unspecified) fuzzy degrees. The answer to queries is, consequently, an algebraic expression involving the (unknown) fuzzy degrees and the degree...

Fuzzy rules for control can be eeectively tuned via reinforcement learning. Reinforcement learning is a weak learning method, which only requires information on the success or failure of the control application. The tuning process allows people to generate fuzzy rules which are unable to accurately perform control and have them tuned to be rules which provide smooth control. This paper explores...

In the social decision making context, a manipulator attempts to change the social choice in his favor by misrepresenting his preferences. Gibbard and Satterthwaite [7,10] established independently that a strategic manipulation can be observed when using any non-dictatorial voting choice procedure. In this paper, we are interested in the manipulation of the social choice when individuals reveal...

Many ranking methods have been proposed so far. The fuzzy number defuzzification method with continuous weighted quasi-arithmetic means was proposed by Yoshida in the domain (−∞,+∞) . Recently in [22], the researcher used this method with the ordinary fuzzy set in a compact interval, that all the conclusions can be extended to the ordinary fuzzy set in [24] directly. This parameterized defuzzif...

The successful application of fuzzy reasoning models to fuzzy control systems depends on a number of parameters, such as fuzzy membership functions, that are usually decided upon subjectively. It is shown in this paper that the performance of fuzzy control systems may be improved if the fuzzy reasoning model is supplemented by a genetic-based learning mechanism. The genetic algorithm enables us...

Fuzzy models have been designed to represent approximate or imprecise relationships in complex systems and have been successfully employed in control systems, expert systems, and decision analysis. Classically, fuzzy models were built from human expertise and knowledge of the system being modeled. As systems have grown more complex it has become increasingly difficult to construct models direct...

Fuzzy Description Logics (DLs) are logics that allow to deal with structured vague knowledge. Although a relatively important amount of work has been carried out in the last years concerning the use of fuzzy DLs as ontology languages, the problem of automatically managing the evolution of fuzzy ontologies has received very little attention so far. We describe here a logic-based computational me...

Exploring the growing interest in extending the theory of probability and statistics to allow for more flexible modeling of uncertainty, ignorance, and fuzziness, the properties of fuzzy modeling are investigated for statistical signals, which benefit from the properties of fuzzy modeling. There is relatively research in the area, making explicit identification of statistical/stochastic fuzzy m...