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Rule-base self-generation and simplification for data-driven fuzzy models

โœ Scribed by Min-You Chen; D.A. Linkens

Publisher
Elsevier Science
Year
2004
Tongue
English
Weight
573 KB
Volume
142
Category
Article
ISSN
0165-0114

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๐Ÿ“œ SIMILAR VOLUMES

Rule-base self-generation and simplifica
Rule-base self-generation and simplification for data-driven fuzzy models
โœ Min-You Chen; D.A. Linkens ๐Ÿ“‚ Article ๐Ÿ“… 2004 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 573 KB

Data-driven fuzzy modeling has been used in a wide variety of applications. However, in fuzzy rule-based models acquired from numerical data, redundancy often exists in the form of redundant rules or similar fuzzy sets. This results in unnecessary structural complexity and decreases the interpretabi

An alternative approach for generation o
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The theoretically attractive fact that the radial basis function networks can be interpreted as fuzzy systems is of small importance for practical applications such as diagnosis and quality control with large numbers of inputs or hidden neurons, due to the lack of transparency of the resulting fuzzy