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2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011)

27-30 June 2011

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Displaying Results 1 - 25 of 449
  • [Title page]

    Publication Year: 2011, Page(s): 1
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  • [Copyright notice]

    Publication Year: 2011, Page(s): 2
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  • Table of contents

    Publication Year: 2011, Page(s): 1
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  • A message from the conference organizers

    Publication Year: 2011, Page(s): 4
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  • Committees

    Publication Year: 2011, Page(s):5 - 9
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  • Special session organizers

    Publication Year: 2011, Page(s):10 - 12
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  • List of reviewers

    Publication Year: 2011, Page(s):13 - 17
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  • Tutorials

    Publication Year: 2011, Page(s):18 - 34
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (109 KB)

    Provides an abstract for each of the tutorial presentations and a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings. View full abstract»

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  • Panel sessions

    Publication Year: 2011, Page(s):35 - 39
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  • An extension of a fuzzy ontology for flexible querying

    Publication Year: 2011, Page(s):2033 - 2038
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (180 KB) | HTML iconHTML

    In this paper, we propose a personalized approach for flexible querying of information systems. This approach consists in the combination of the reasoning capabilities of the fuzzy DLR-Lite ontology and the expressivity of the SQLf language. The interpretation of the gradual inclusion (subsumption) axioms of the ontology is based on the Godel fuzzy implication. Its generalization to a tree of incl... View full abstract»

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  • On a strengthening connective for flexible database querying

    Publication Year: 2011, Page(s):1233 - 1238
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (192 KB) | HTML iconHTML

    In most of query languages, conjunctive and disjunctive combinations of conditions remain the usual way for aggregation. Fuzzy query languages also offer trade-off operators, such as means in order to compensate between elementary conditions. In this paper, we investigate a new type of condition basically founded on the interaction between two predicates, thus enriching the panoply of tools the us... View full abstract»

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  • On the geometry of join and meet calculations for general type-2 fuzzy sets

    Publication Year: 2011, Page(s):2407 - 2413
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (433 KB) | HTML iconHTML

    The union and intersection of general type-2 fuzzy sets (T2 FSs) are fundamental computations for such FSs. In the past, algorithms were developed for the union and intersection computations using vertical-slice and horizontal-slice representations of T2 FSs. The vertical-slice representation of a T2 FS traces its origins back to Zadeh [32] and requires computing the join or meet, whereas the hori... View full abstract»

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  • Optimal static output feedback control of fuzzy-model-based control systems

    Publication Year: 2011, Page(s):1774 - 1777
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (167 KB) | HTML iconHTML

    By integrating the stabilizability condition, the orthogonal-functions approach (OFA), and the hybrid Taguchi-genetic algorithm (HTGA), an integrative method is presented in this paper to design the stable and quadratic-optimal static output feedback parallel-distributed-compensation (PDC) controller such that (i) the Takagi-Sugeno (TS) fuzzy-model-based control system can be stabilized, and (ii) ... View full abstract»

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  • Evaluate and identify optimal weapon systems using fuzzy multiple criteria decision making

    Publication Year: 2011, Page(s):1510 - 1515
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (658 KB) | HTML iconHTML

    The weapon identification and selection issue is an important and strategic component and has a significant impact on the efficiency of defense system in US. The main purpose of this research is to develop a universal model and system to effectively assess, evaluate and identify the optimal weapons from a large collection of available weapon systems that have multiple criteria based on a fuzzy mul... View full abstract»

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  • PCA-guided k-Means clustering with incomplete data

    Publication Year: 2011, Page(s):1710 - 1714
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (170 KB) | HTML iconHTML

    This paper considers k-Means clustering of incomplete data sets including missing values. Although the main purpose of k-Means clustering is to partition samples into several homogeneous clusters by minimizing within-cluster errors, it has been shown that a relaxed solution of k-Means can be recovered in a PCA-guided manner. In this paper, the PCA-guided k-Means procedure is extended to a situatio... View full abstract»

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  • Re-scheduling the unit commitment problem in fuzzy environment

    Publication Year: 2011, Page(s):1090 - 1095
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (166 KB) | HTML iconHTML

    The conventional prediction of future power demands are always made based on the historical data. However, the real power demands are affected by many other factors as weather, temperature and unexpected emergencies. The use of historical information alone cannot well predict real future demands. In this study, the experts' opinions from related fields are taken into consideration. To deal the unc... View full abstract»

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  • Building a fuzzy multi-objective portfolio selection model with distinct risk measurements

    Publication Year: 2011, Page(s):1096 - 1102
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (274 KB) | HTML iconHTML

    Based on portfolio selection theory, this study pro poses an improved fuzzy multi-objective model that can evaluate the invest risk exactly and increase the probability of obtaining the expected return. In building the model, fuzzy Value-at-Risk (VaR) is used to evaluate the exact future risk, in term of loss. The VaR can directly reflect the greatest loss of a selection case under a given confide... View full abstract»

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  • Direct adaptive fuzzy control for nonaffine nonlinear systems with unknown control direction

    Publication Year: 2011, Page(s):2870 - 2875
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (204 KB) | HTML iconHTML

    This paper deals with direct adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems with unknown control direction. Within this scheme, a fuzzy system is used to generate directly the control input signal without dynamic system estimation. The adjustable parameters in the used fuzzy system are updated using a gradient descent adaptation algorithm that incorporates a Nussbaum-t... View full abstract»

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  • A fuzzy hypothesis test based model for customer satisfaction measurement (Case study in PARS KHODRO CO)

    Publication Year: 2011, Page(s):564 - 571
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (251 KB) | HTML iconHTML

    The article proposes a model for customer satisfaction measuring, which is adapted to use in automobile industries. The proposed methodology evaluates the satisfaction level of a set of customers in different aspect of customer focus based on hypothesis values. It permits to evaluate the validity of a service/manufacturing operation from the point of view of consumers. The main advantages of this ... View full abstract»

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  • Comparison and practical implementation of type-reduction algorithms for type-2 fuzzy sets and systems

    Publication Year: 2011, Page(s):2131 - 2138
    Cited by:  Papers (41)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4165 KB) | HTML iconHTML

    Type-reduction algorithms are very important for type-2 fuzzy sets and systems. The earliest one, and also the most popular one, is the Karnik-Mendel Algorithm, which is iterative and computationally intensive. In the last a few years researchers have proposed several other more efficient type-reduction algorithms. In this paper we also propose a new algorithm which improves over the latest result... View full abstract»

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  • Short-term load forecasting via fuzzy neural network with varied learning rates

    Publication Year: 2011, Page(s):2426 - 2431
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1440 KB) | HTML iconHTML

    Due to the lack of natural resources, the majority of energy in many countries must depend on import, and the corresponding cost is expensive and affected by international market fluctuation and control. In recent years, an intelligent microgrid system composed of renewable energy sources is becoming one of the interesting research topics. The forecasting of short-term loads enables the intelligen... View full abstract»

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  • Hypoglycemia detection using fuzzy inference system with genetic algorithm

    Publication Year: 2011, Page(s):2225 - 2231
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (249 KB) | HTML iconHTML

    In this paper, we develope a genetic algorithm based fuzzy inference system to recognize hypoglycemic episodes based on heart rate and corrected QT interval of the electrocardiogram (ECG) signal. Genetic algorithm is introduced to optimize the membership functions and fuzzy rules. A practical experiment based on data from 15 children with T1DM is studied. All the data sets are collected from the D... View full abstract»

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  • Permutation flow shop scheduling: Fuzzy particle swarm optimization approach

    Publication Year: 2011, Page(s):572 - 578
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (275 KB) | HTML iconHTML

    A fuzzy particle swarm optimization (PSO) for the minimization of makespan in permutation flow shop scheduling problem is presented in this paper. In the proposed fuzzy PSO, the inertia weight of PSO and the control parameter of the cross mutated operation are determined by a set of fuzzy rules. To escape the local optimum, cross-mutated operation is introduced. In order to make PSO suitable for s... View full abstract»

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  • Determination of process conditions of epoxy dispensing processes using a genetic algorithm based neural fuzzy networks

    Publication Year: 2011, Page(s):2253 - 2260
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (237 KB) | HTML iconHTML

    In this paper, process conditions of epoxy dispensing processes are determined by the proposed genetic algorithm based neural fuzzy networks, which consists of two tasks: a) the approach of neural fuzzy networks, which was shown to be better than the other existing approaches, is proposed to develop models in relating between process parameters and quality characteristics for the epoxy dispensing ... View full abstract»

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  • Manufacturing modeling using an evolutionary fuzzy regression

    Publication Year: 2011, Page(s):2261 - 2267
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (188 KB) | HTML iconHTML

    Fuzzy regression is a commonly used approach for modeling manufacturing processes in which the availability of experimental data is limited. Fuzzy regression can address fuzzy nature of experimental data in which fuzziness is not avoidable while carrying experiments. However, fuzzy regression can only address linearity in manufacturing process systems, but nonlinearity, which is unavoidable in the... View full abstract»

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