In Mixed Fuzzy Rule Formation [Int. J. Approx. Reason. 32 (2003) 67] a method to extract mixed fuzzy rules from data was introduced. The underlying algorithm s performance is influenced by the choice of fuzzy t-norm and t-conorm, and a heuristic to avoid conflicts between patterns and rules of different classes throughout training. In the following addendum to [Int. J. Approx. Reason. 32 (2003) 67], we discuss in more depth how these parameters affect the generalization performance of the resulting fuzzy rule models
This paper shows how a small number of fuzzy rules can be selected for designing interpretable fuzzy...
An objective of merging rules in rule bases designed for system modeling and function approximation ...
The characteristics of a fuzzy model are frequently determined by the manner in which the rules are ...
AbstractIn Mixed Fuzzy Rule Formation [Int. J. Approx. Reason. 32 (2003) 67] a method to extract mix...
We hereby correct an error in Ref. [2], in which we studied the influence of various parameters that...
Many fuzzy rule induction algorithms have been pro-posed during the past decade or so. Most of these...
Many fuzzy rule induction algorithms have been proposed during the past decade or so. Most of these ...
AbstractMany fuzzy rule induction algorithms have been proposed during the past decade or so. Most o...
AbstractFuzzy Rule-Based Systems have been succesfully applied to pattern classification problems. I...
This paper briefly reviews techniques for learning fuzzy rules. In many applications fuzzy if-then r...
The structure of fuzzy models produced by a heursitic analysis of the problem domain is compared wit...
The characteristics of a fuzzy model are frequently influenced by the method used to construct the r...
Abstract. This paper compares heuristic criteria used for extracting a pre-specified number of fuzzy...
AbstractProcessing information in fuzzy rule-based systems generally employs one of two patterns of ...
Summary. In this work we propose the hybridization of two techniques to improve the cooperation amon...
This paper shows how a small number of fuzzy rules can be selected for designing interpretable fuzzy...
An objective of merging rules in rule bases designed for system modeling and function approximation ...
The characteristics of a fuzzy model are frequently determined by the manner in which the rules are ...
AbstractIn Mixed Fuzzy Rule Formation [Int. J. Approx. Reason. 32 (2003) 67] a method to extract mix...
We hereby correct an error in Ref. [2], in which we studied the influence of various parameters that...
Many fuzzy rule induction algorithms have been pro-posed during the past decade or so. Most of these...
Many fuzzy rule induction algorithms have been proposed during the past decade or so. Most of these ...
AbstractMany fuzzy rule induction algorithms have been proposed during the past decade or so. Most o...
AbstractFuzzy Rule-Based Systems have been succesfully applied to pattern classification problems. I...
This paper briefly reviews techniques for learning fuzzy rules. In many applications fuzzy if-then r...
The structure of fuzzy models produced by a heursitic analysis of the problem domain is compared wit...
The characteristics of a fuzzy model are frequently influenced by the method used to construct the r...
Abstract. This paper compares heuristic criteria used for extracting a pre-specified number of fuzzy...
AbstractProcessing information in fuzzy rule-based systems generally employs one of two patterns of ...
Summary. In this work we propose the hybridization of two techniques to improve the cooperation amon...
This paper shows how a small number of fuzzy rules can be selected for designing interpretable fuzzy...
An objective of merging rules in rule bases designed for system modeling and function approximation ...
The characteristics of a fuzzy model are frequently determined by the manner in which the rules are ...