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# IEEE Transactions on Fuzzy Systems

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Displaying Results 1 - 25 of 28

Publication Year: 2008, Page(s):C1 - 1389
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• ### IEEE Transactions on Fuzzy Systems publication information

Publication Year: 2008, Page(s): C2
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• ### Guest Editorial Evolving Fuzzy Systems–-Preface to the Special Section

Publication Year: 2008, Page(s):1390 - 1392
Cited by:  Papers (15)
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First Page of the Article
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• ### FLEXFIS: A Robust Incremental Learning Approach for Evolving Takagi–Sugeno Fuzzy Models

Publication Year: 2008, Page(s):1393 - 1410
Cited by:  Papers (139)  |  Patents (1)
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In this paper, we introduce a new algorithm for incremental learning of a specific form of Takagi-Sugeno fuzzy systems proposed by Wang and Mendel in 1992. The new data-driven online learning approach includes not only the adaptation of linear parameters appearing in the rule consequents, but also the incremental learning of premise parameters appearing in the membership funct... View full abstract»

• ### A Self-Evolving Interval Type-2 Fuzzy Neural Network With Online Structure and Parameter Learning

Publication Year: 2008, Page(s):1411 - 1424
Cited by:  Papers (121)
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This paper proposes a self-evolving interval type-2 fuzzy neural network (SEIT2FNN) with online structure and parameter learning. The antecedent parts in each fuzzy rule of the SEIT2FNN are interval type-2 fuzzy sets and the fuzzy rules are of the Takagi-Sugeno-Kang (TSK) type. The initial rule base in the SEIT2FNN is empty, and the online clustering method is proposed to generate fuzzy rules that... View full abstract»

• ### Incremental Evolution of Fuzzy Grammar Fragments to Enhance Instance Matching and Text Mining

Publication Year: 2008, Page(s):1425 - 1438
Cited by:  Papers (15)
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In many applications, it is useful to extract structured data from sections of unstructured text. A common approach is to use pattern matching (e.g., regular expressions) or more general grammar-based techniques. In cases where exact templates or grammar fragments are not known, it is possible to use machine learning approaches, based on words or n-grams, to identify the structured data. This is g... View full abstract»

• ### An Evolving Fuzzy Predictor for Industrial Applications

Publication Year: 2008, Page(s):1439 - 1449
Cited by:  Papers (21)
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A reliable and online predictor is very useful to a wide array of industries to forecast the behavior of time-varying dynamic systems. In this paper, an evolving fuzzy system (EFS) is developed for system state forecasting. An evolving clustering algorithm is proposed for cluster generation. Clusters are established and modified based on constraint criteria of mapping consistence and compatible me... View full abstract»

• ### Fully Evolvable Optimal Neurofuzzy Controller Using Adaptive Critic Designs

Publication Year: 2008, Page(s):1450 - 1461
Cited by:  Papers (22)
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A near-optimal neurofuzzy external controller is designed in this paper for a static compensator (STATCOM) in a multimachine power system. The controller provides an auxiliary reference signal for the STATCOM in such a way that it improves the damping of the rotor speed deviations of its neighboring generators. A zero-order Takagi-Sugeno fuzzy rule base constitutes the core of the controller. A he... View full abstract»

• ### Evolving Fuzzy-Rule-Based Classifiers From Data Streams

Publication Year: 2008, Page(s):1462 - 1475
Cited by:  Papers (144)
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A new approach to the online classification of streaming data is introduced in this paper. It is based on a self-developing (evolving) fuzzy-rule-based (FRB) classifier system of Takagi-Sugeno ( eTS) type. The proposed approach, called eClass (evolving class ifier), includes different architectures and online learning methods. The family of alternat... View full abstract»

• ### Efficient Self-Evolving Evolutionary Learning for Neurofuzzy Inference Systems

Publication Year: 2008, Page(s):1476 - 1490
Cited by:  Papers (14)
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This study proposes an efficient self-evolving evolutionary learning algorithm (SEELA) for neurofuzzy inference systems (NFISs). The major feature of the proposed SEELA is that it is based on evolutionary algorithms that can determine the number of fuzzy rules and adjust the NFIS parameters. The SEELA consists of structure learning and parameter learning. The structure learning attempts to determi... View full abstract»

• ### Fuzzy Turing Machines: Variants and Universality

Publication Year: 2008, Page(s):1491 - 1502
Cited by:  Papers (7)
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In this paper, we study some variants of fuzzy Turing machines (FTMs) and universal FTM. First, we give several formulations of FTMs, including, in particular, deterministic FTMs (DFTMs) and nondeterministic FTMs (NFTMs). We then show that DFTMs and NFTMs are not equivalent as far as the power of recognizing fuzzy languages is concerned. This contrasts sharply with classical TMs. Second, we show t... View full abstract»

• ### Encoding Words Into Interval Type-2 Fuzzy Sets Using an Interval Approach

Publication Year: 2008, Page(s):1503 - 1521
Cited by:  Papers (117)
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This paper presents a very practical type-2-fuzzistics methodology for obtaining interval type-2 fuzzy set (IT2 FS) models for words, one that is called an interval approach (IA). The basic idea of the IA is to collect interval endpoint data for a word from a group of subjects, map each subject's data interval into a prespecified type-1 (T1) person membership function, interpret the latter as an e... View full abstract»

• ### A Fuzzy Qualitative Framework for Connecting Robot Qualitative and Quantitative Representations

Publication Year: 2008, Page(s):1522 - 1530
Cited by:  Papers (48)
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This paper proposes a novel framework for describing articulated robot kinematics motion with the goal of providing a unified representation by combining symbolic or qualitative functions and numerical sensing and control tasks in the context of intelligent robotics. First, fuzzy qualitative robot kinematics that provides theoretical preliminaries for the proposed robot motion representation is re... View full abstract»

• ### Domain Representation Using Possibility Theory: An Exploratory Study

Publication Year: 2008, Page(s):1531 - 1541
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This study explores a new domain representation method for natural language processing based on an application of possibility theory. In our method, domain-specific information is extracted from natural language documents using a mathematical process based on Rieger's notion of semantic distances, and represented in the form of possibility distributions. We implement the distributions in the conte... View full abstract»

• ### An Efficient Pruning Method for Decision Alternatives of OWA Operators

Publication Year: 2008, Page(s):1542 - 1549
Cited by:  Papers (5)
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In this paper, we present an efficient method for pruning decision alternatives in the case of using ordered weighted averaging (OWA) operators for decision making. The proposed method helps to identify inferior alternatives that are less likely to be selected out of competing alternatives as the OWA aggregation proceeds. It thus enables us to diminish the number of alternatives before applying th... View full abstract»

• ### Perceptual Reasoning for Perceptual Computing

Publication Year: 2008, Page(s):1550 - 1564
Cited by:  Papers (42)
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In 1996, Zadeh proposed the paradigm of computing with words (CWW). A specific architecture for making subjective judgments using CWW was proposed by Mendel in 2001. It is called a Perceptual Computer (Per-C), and because words can mean different things to different people, it uses interval type-2 fuzzy set (IT2 FS) models for all words. The Per-C has three eleme... View full abstract»

• ### Fuzzy Clustering and Aggregation of Relational Data With Instance-Level Constraints

Publication Year: 2008, Page(s):1565 - 1581
Cited by:  Papers (12)
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In this paper, we introduce a semisupervised approach for clustering and aggregating relational data (SS-CARD). We assume that data is available in a relational form, where information only about the degrees to which pairs of objects in the dataset are related is available. Moreover, we assume that the relational information is represented by multiple dissimilarity matrices. These matrices ... View full abstract»

• ### Performance of the IDS Method as a Soft Computing Tool

Publication Year: 2008, Page(s):1582 - 1596
Cited by:  Papers (7)
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Performance factors such as robustness, speed, and tractability are important for the realization of practical computing systems. The aim of soft computing is to achieve these factors in practice by tolerating imprecision and uncertainty instead of depending on exact mathematical computations. The ink drop spread (IDS) method is a modeling technique that has been proposed as a new approach to soft... View full abstract»

• ### A Hammerstein Recurrent Neurofuzzy Network With an Online Minimal Realization Learning Algorithm

Publication Year: 2008, Page(s):1597 - 1612
Cited by:  Papers (5)
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This paper presents a Hammerstein recurrent neurofuzzy network associated with an online minimal realization learning algorithm for dealing with nonlinear dynamic applications. We fuse the concept of states in linear systems into a neurofuzzy framework so that the whole structure can be expressed by a state-space representation. An online minimal realization learning algorithm has been developed t... View full abstract»

• ### Analytical Study and Stability Design of a 3-D Fuzzy Logic Controller for Spatially Distributed Dynamic Systems

Publication Year: 2008, Page(s):1613 - 1625
Cited by:  Papers (13)
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A novel 3-D fuzzy logic controller (3-D FLC) was presented to control a class of spatially distributed dynamic systems by Li (IEEE Trans. Fuzzy Syst., vol. 15, no. 3, pp. 470-481, Jun. 2007) by utilizing a 3-D fuzzy set and an inference mechanism with 3-D nature for spatial information processing. In this paper, the analytical mathematical model of the 3-D FLC is derive... View full abstract»

• ### Fuzzy Interpolative Reasoning for Sparse Fuzzy Rule-Based Systems Based on ${bm alpha}$-Cuts and Transformations Techniques

Publication Year: 2008, Page(s):1626 - 1648
Cited by:  Papers (57)
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In sparse fuzzy rule-based systems, the fuzzy rule bases are usually incomplete. In this situation, the system may not properly perform fuzzy reasoning to get reasonable consequences. In order to overcome the drawback of sparse fuzzy rule-based systems, there is an increasing demand to develop fuzzy interpolative reasoning techniques in sparse fuzzy rule-based systems. In this paper, we present a ... View full abstract»

• ### Piecewise $H_{infty}$ Controller Design of Uncertain Discrete-Time Fuzzy Systems With Time Delays

Publication Year: 2008, Page(s):1649 - 1655
Cited by:  Papers (18)
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This paper considers the robust H infin control of uncertain discrete-time fuzzy systems with time delays based on piecewise Lyapunov--Krasovskii functionals. It is shown that the stability with H infin disturbance attenuation performance can be established for the closed-loop fuzzy control systems if there exists a piecewise Lyapunov--Krasovskii functional, and... View full abstract»

• ### ${cal H}_{infty}$ State-Feedback Control Design for Fuzzy Systems Using Lyapunov Functions With Quadratic Dependence on Fuzzy Weighting Functions

Publication Year: 2008, Page(s):1655 - 1663
Cited by:  Papers (8)
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This paper proposes a method for designing an Hinfin state-feedback fuzzy controller for discrete-time Takagi-Sugeno (T-S) fuzzy systems. To derive less conservative Hinfin stabilization conditions, this paper enhances the interactions among the fuzzy subsystems using a multiple Lyapunov function with quadratic dependence on fuzzy weighting functions. Besides, for more alloca... View full abstract»

• ### Corrections to “Aggregation Using the Linguistic Weighted Average and Interval Type-2 Fuzzy Sets”

Publication Year: 2008, Page(s):1664 - 1666
Cited by:  Papers (31)
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In the previous paper, we have proposed linguistic weighted average (LWA) algorithms that can be used in distributed and hierarchical decision making. The original LWA algorithms were completely based on the representation theorem for interval type-2 fuzzy sets (IT2 FSs). In later usage, we found that when the lower membership functions (LMFs) of the inputs and weights are of different heights, th... View full abstract»

• ### 2008 Index IEEE Transactions on Fuzzy Systems Vol. 16

Publication Year: 2008, Page(s):1667 - 1683
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## Aims & Scope

The IEEE Transactions on Fuzzy Systems (TFS) is published bimonthly. TFS will consider papers that deal with the theory, design or an application of fuzzy systems ranging from hardware to software.

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## Meet Our Editors

Editor-in-Chief
Jonathan Garibaldi
University of Nottingham
Nottingham NG8 1BB, U.K.
jon.garibaldi@nottingham.ac.uk
Phone: +44 115 95 14216
Fax: +44 115 95 14799