A STUDY ABOUT THE INCLUSION OF LINGUISTIC HEDGES IN A FUZZY RULE LEARNING ALGORITHM
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Publication:5469453
DOI10.1142/S0218488599000192zbMath1087.68615OpenAlexW2067259407MaRDI QIDQ5469453
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Publication date: 19 May 2006
Published in: International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1142/s0218488599000192
Learning and adaptive systems in artificial intelligence (68T05) Reasoning under uncertainty in the context of artificial intelligence (68T37)
Related Items (4)
A MULTI-OBJECTIVE GENETIC ALGORITHM FOR TUNING AND RULE SELECTION TO OBTAIN ACCURATE AND COMPACT LINGUISTIC FUZZY RULE-BASED SYSTEMS ⋮ Linguistic modeling with hierarchical systems of weighted linguistic rules ⋮ Fuzzy Modifiers at the Core of Interpretable Fuzzy Systems ⋮ Genetic learning of the membership functions for mining fuzzy association rules from low quality data
Cites Work
- A fuzzy logic controller with learning through the evolution of its knowledge base
- Adapting the gain of an FLC with genetic algorithms
- A three-stage evolutionary process for learning descriptive and approximate fuzzy-logic-controller knowledge bases from examples.
- The concept of a linguistic variable and its application to approximate reasoning. I
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