Similarity measures in fuzzy rule base simplification
β Scribed by Setnes, M.; Babuska, R.; Kaymak, U.; van Nauta Lemke, H.R.
- Book ID
- 117874406
- Publisher
- IEEE
- Year
- 1998
- Tongue
- English
- Weight
- 316 KB
- Volume
- 28
- Category
- Article
- ISSN
- 1083-4419
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π SIMILAR VOLUMES
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
The work described in this paper proposes a method for the measurement of similarity, viewed from the decision maker's perspective. At first, an algorithm is presented that generalizes a discrete fuzzy set F, representing a model, given another discrete fuzzy set G representing new evidence. The alg