First, we introduce the concept of intuitionistic fuzzy group congruenceand we obtain the characterizations of intuitionistic fuzzy group congruenceson an inverse semigroup and a T^{*}-pure semigroup, respectively. Also,we study some properties of intuitionistic fuzzy group congruence. Next, weintroduce the notion of intuitionistic fuzzy semilattice congruence and we givethe characterization of...

This paper studies the H control problem for a nonlinear large-scale system with unknown disturbance. In the large-scale system, each subsystem “without” nonlinear interconnections and disturbance is transformed into a T-S fuzzy system. Moreover, based on a linear decomposition, the nonlinear interconnection corresponding to each subsystem is decomposed to a linear weighting interconnection wh...

In this paper the behavior of three combinational rules for temporal/sequential attribute data fusion for target type estimation are analyzed. The comparative analysis is based on: Dempster’s fusion rule proposed in Dempster-Shafer Theory; Proportional Conflict Redistribution rule no. 5 (PCR5), proposed in Dezert-Smarandache Theory and one alternative class fusion rule, connecting the combinati...

This paper is concerned with the application of a treebased regression model to extract fuzzy rules from highdimensional data. We introduce a locally weighted scheme to the identification of Takagi-Sugeno type rules. It is proposed to apply the sequential least-squares method to estimate the linear model. A hierarchical clustering takes place in the product space of systems inputs and outputs a...

In today‟s world, fuzzy logic and particle swarm optimization are used to answer various engineering problems. In this paper, the proportional integral derivative (PID) controller tuning by fuzzy rule method (FRMs) and a particle swarm optimization (PSO) algorithm are proposed to improve controller by adjusting transfer function parameters. The proposed fuzzy rule function and PSO algorithm sea...

A Neural integrated Fuzzy conTroller (NiF-T) which integrates the fuzzy logic representation of human knowledge with the learning capability of neural networks is developed for nonlinear dynamic control problems. NiF-T architecture comprises of three distinct parts: (1) Fuzzy logic Membership Functions (FMF), (2) a Rule Neural Network (RNN), and (3) an Output-Refinement Neural Network (ORNN). F...

Sophisticated fuzzy rule systems are supposed to be flexible, complete, consistent and compact (FC). Flexibility, completeness and consistency are essential for fuzzy systems to exhibit an excellent performance and to have a clear physical meaning, while compactness is crucial when the number of the input variables increases. However, the completeness and consistency conditions are often violat...

this paper investigates existence and uniqueness results for the first order fuzzy integro-differential equations. then numerical results and error bound based on the left rectangular quadrature rule, trapezoidal rule and a hybrid of them are obtained. finally an example is given to illustrate the performance of the methods.

Fuzzy systems working with a sparse rule base apply special reasoning techniques in order to ensure the acceptable output in case of observations hitting the gap between the antecedent parts of the rules, too. The methods that follow the generalized methodology of the fuzzy rule interpolation (GM) [1] produce the conclusion in two steps. First a new rule is interpolated in the position determin...

Combining intuitionistic fuzzy sets and filter theory,we studied interval valued intuitionistic (T, S)-fuzzy filters on lattice implication algebras. some relation properties of it are obtained, the relation between intuitionistic (T, S)-fuzzy filters and intuitionistic fuzzy set are discussed.The investigation method and content of lattice implication algebras are extended. Mathematics Subject...