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TFS
2008
90views more  TFS 2008»
13 years 7 months ago
Fuzzy Interpolation and Extrapolation: A Practical Approach
Fuzzy interpolation does not only help to reduce the complexity of fuzzy models, but also makes inference in sparse rule-based systems possible. It has been successfully applied to...
Zhiheng Huang, Qiang Shen
TFS
2008
112views more  TFS 2008»
13 years 7 months ago
Gradual Numbers and Their Application to Fuzzy Interval Analysis
Abstract-- We introduce a new way of looking at fuzzy intervals. Instead of considering them as fuzzy sets, we see them as crisp sets of entities we call gradual (real) numbers. Th...
Jérôme Fortin, Didier Dubois, H&eacut...
EUSFLAT
2009
158views Fuzzy Logic» more  EUSFLAT 2009»
13 years 5 months ago
Bi-criteria Genetic Selection of Bagging Fuzzy Rule-based Multiclassification Systems
Previously we proposed a scheme to generate fuzzy rule-based multiclassification systems by means of bagging, mutual information-based feature selection, and a multicriteria geneti...
Krzysztof Trawinski, Arnaud Quirin, Oscar Cord&oac...
AUTOMATICA
2005
152views more  AUTOMATICA 2005»
13 years 7 months ago
Identification of dynamical systems with a robust interval fuzzy model
In this paper we present a new method of interval fuzzy model identification. The method combines a fuzzy identification methodology with some ideas from linear programming theory...
Igor Skrjanc, Saso Blazic, Osvaldo E. Agamennoni
EUSFLAT
2001
104views Fuzzy Logic» more  EUSFLAT 2001»
13 years 9 months ago
Iterative learning fuzzy control
In this paper an iterative learning control design method is depicted, leading to a feedforward controller minimizing tracking error of repetitive trajectories. The approach is ex...
Manuel Olivares, Pedro Albertos, Antonio Sala