This paper pre sents a new algorithm for constructing fuzzy de cision tree s from relational database systems and gene rating fuzzy rule s from the constructed fuzzy de cision tre es. We also pre sent a me thod for dealing with the comple tene ss of the constructed fuzzy decision tree s. Based on the gene rated fuzzy rule s, we also pre sent a method for e stimating null values in re lational d...

fuzzy newton-cotes method for integration of fuzzy functions that was proposed by ahmady in [1]. in this paper we construct error estimate of fuzzy newton-cotes method such as fuzzy trapezoidal rule and fuzzy simpson rule by using taylor's series. the corresponding error terms are proven by two theorems. we prove that the fuzzy trapezoidal rule is accurate for fuzzy polynomial of degree one and...

Fuzzy Newton-Cotes method for integration of fuzzy functions that was proposed by Ahmady in [1]. In this paper we construct error estimate of fuzzy Newton-Cotes method such as fuzzy Trapezoidal rule and fuzzy Simpson rule by using Taylor's series. The corresponding error terms are proven by two theorems. We prove that the fuzzy Trapezoidal rule is accurate for fuzzy polynomial of degree one and...

This paper deals with the design of a fuzzy controller (FC) based on pole assignment method for the control of a liquid level system. The problem is to control level set point changes by adjusting the flowrate of liquid entering the tank through a feed pump [2], [5]. The behaviour of the closed loop fuzzy system controlled by the fuzzy controller is identical to the linear system whose state tr...

In this chapter, a class of nonlinear time-delay systems based on the TakagiŽ . w x Sugeno T-S fuzzy model is defined 1 . We investigate the delay-independent stability of this model. A model-based fuzzy stabilization design utilizing Ž . the concept of parallel distributed compensation PDC is employed. The main idea of the controller design is to derive each control rule to compensate each rul...

Rule-driven processing is a proven way of achieving high-speed in fuzzy processing. Up to now, ruledriven architectures where designed to work with minimum or product as T-norm. Nevertheless, a Lukasiewicz T-norm is typically used with the compositional rule of inference in expert systems applications that are based on a fuzzy inference engine. This paper presents a rule-driven processing archi...

Fuzzy rule based classification systems are one of the most popular fuzzy modeling systems used in pattern classification problems. This paper investigates the effect of applying nine different T-norms in fuzzy rule based classification systems. In the recent researches, fuzzy versions of confidence and support merits from the field of data mining have been widely used for both rules selecting ...

In 1965 Lofti A. Zadeh proposed fuzzy sets as a generalization of crisp (or classic) sets to address the incapability of crisp sets to model uncertainty and vagueness inherent in the real world. Initially, fuzzy sets did not receive a very warm welcome as many academics stood skeptical towards a theory of “imprecise” mathematics. In the middle to late 1980’s the success of fuzzy controllers bro...

Fuzzy classification rules allow the definition of readable and interpretable rule bases. Nevertheless, the shape of the resulting class borders of fuzzy classification rules depends to a great part on the used tnorm and t-conorm and can sometimes even be counter-intuitive. In this paper we discuss the shape of class borders between overlapping rules under consideration of different t-norms and...

This paper proposes an approach to fuzzy modeling of magnetic levitation systems. These unstable and nonlinear processes are first linearized around several operating points, and next stabilized by a State Feedback Control System (SFCS) structure. Discrete-time Takagi-Sugeno (T-S) fuzzy models of the stabilized processes are derived on the basis of the modal equivalence principle, and the rule ...