IEEE Transactions on Fuzzy Systems

In the above paper by Cordon and Herrara (IEEE Trans. Fuzzy Syst., vol. 8, p. 335-44, 2000), the so-called accurate linguistic modeling (ALM) method was proposed to improve the accuracy of linguistic fuzzy models. A number of examples are given to demonstrate the benefits of the approach. We show that: 1) these examples are not suitable as benchmarks or demonstrators of nonlinear modeling techniqu... View full abstract»

To design a fuzzy rule-based classification system (fuzzy classifier) with good generalization ability in a high dimensional feature space has been an active research topic for a long time. As a powerful machine learning approach for pattern recognition problems, the support vector machine (SVM) is known to have good generalization ability. More importantly, an SVM can work very well on a high- (o... View full abstract»

Fuzzy clustering helps to find natural vague boundaries in data. The fuzzy c-means method is one of the most popular clustering methods based on minimization of a criterion function. Among many existing modifications of this method, conditional or context-dependent c-means is the most interesting one. In this method, data vectors are clustered under conditions based on linguistic terms represented... View full abstract»

In our opinion, there are two main concerns in Roubos and Babugka's note, that are summarized as follows. 1) The kinds of problems used in our paper to test the algorithm proposed in "A proposal to improve the accuracy of linguistic modeling" and other studies. The authors claim that they are very simple to be considered as benchmarks for nonlinear modeling techniques. 2) The interpretability of t... View full abstract»

In this paper, the so-called Wang-Mendel (WM) method for generating fuzzy rules from data is enhanced to make it a comprehensive and flexible fuzzy system approach to data description and prediction. In the description part, the core ideas of the WM method are used to develop three methods to extract fuzzy IF-THEN rules from data. The first method shows how to extract rules for the user-specified ... View full abstract»

Boosting is recognized as one of the most successful techniques for generating classifier ensembles. Typically, the classifier outputs are combined by the weighted majority vote. The purpose of this study is to demonstrate the advantages of some fuzzy combination methods for ensembles of classifiers designed by Boosting. We ran two-fold cross-validation experiments on six benchmark data sets to co... View full abstract»

An adaptive fuzzy robust tracking control (AFRTC) algorithm is proposed for a class of nonlinear systems with the uncertain system function and uncertain gain function, which are all the unstructured (or nonrepeatable) state-dependent unknown nonlinear functions arising from modeling errors and external disturbances. The Takagi-Sugeno type fuzzy logic systems are used to approximate unknown uncert... View full abstract»

Computing with words (CW) as a methodology, means computing and reasoning by the use of words in place of numbers or symbols, which may conform more to humans' perception when describing real-world problems. In this paper, as a continuation of a previous paper, we aim to develop and deepen a formal aspect of CW. According to the previous paper, the basic point of departure is that CW treats certai... View full abstract»

In general, fuzzy control design for stochastic nonlinear systems is still difficult since the fuzzy bases are stochastic so as to increase the difficulty and complexity of the fuzzy tracking control design. In this study, a fuzzy stochastic moving-average model with control input (fuzzy ARMAX model) is introduced to describe nonlinear stochastic systems. From the fuzzy ARMAX model, a fuzzy one-st... View full abstract»

We discuss the role of disjunctive aggregation operators in prototype based reasoning systems such as recommender systems. We indicate a need for these aggregation operators to have the additional property of noble reinforcement: Allowing a collection of high valued arguments to reinforce each other to give complete satisfaction while avoiding the situation in which a collection of low valued argu... View full abstract»

This paper investigates the possible applications of dynamical fuzzy systems to control nonlinear plants with asymptotically stable zero dynamics using a fuzzy nonlinear internal model control strategy. The developed strategy consists in including a dynamical Takagi-Sugeno fuzzy model of the plant within the control structure. In this way, the controller design simply results in a fuzzy model inve... View full abstract»

In this paper, the problems of quadratic stability conditions and H∞ control designs for Takagi-Sugeno (T-S) fuzzy systems have been studied. First, a new quadratic stability condition, which is more simple than that in a previous paper, has been proposed. Second, two new sufficient conditions in the terms of linear matrix inequalities (LMIs) which guarantee the existence of the s... View full abstract»

Two of the objectives of Internet are to increase network capacity and offer high quality of differentiated services for traffic with real-time and nonreal-time requirements. Differentiated services (Diff-Serv) were established to fulfill such objectives. Up until now, several Diff-Serv schemes have been proposed which, among others, handle drop and delay priorities. These two priorities raise imp... View full abstract»

The problem of identifying the parameters of the constituent local linear models of Takagi-Sugeno fuzzy models is considered. In order to address the tradeoff between global model accuracy and interpretability of the local models as linearizations of a nonlinear system, two multiobjective identification algorithms are studied. Particular attention is paid to the analysis of conflicts between objec... View full abstract»